Publications | Perceiving Systems - Max Planck Institute for Intelligent Systems

126 results (View BibTeX file of all listed publications)

2016

Skinned multi-person linear model

Black, M.J., Loper, M., Mahmood, N., Pons-Moll, G., Romero, J.

December 2016, Application PCT/EP2016/064610 (misc)

Abstract

The invention comprises a learned model of human body shape and pose dependent shape variation that is more accurate than previous models and is compatible with existing graphics pipelines. Our Skinned Multi-Person Linear model (SMPL) is a skinned vertex based model that accurately represents a wide variety of body shapes in natural human poses. The parameters of the model are learned from data including the rest pose template, blend weights, pose-dependent blend shapes, identity- dependent blend shapes, and a regressor from vertices to joint locations. Unlike previous models, the pose-dependent blend shapes are a linear function of the elements of the pose rotation matrices. This simple formulation enables training the entire model from a relatively large number of aligned 3D meshes of different people in different poses. The invention quantitatively evaluates variants of SMPL using linear or dual- quaternion blend skinning and show that both are more accurate than a Blend SCAPE model trained on the same data. In a further embodiment, the invention realistically models dynamic soft-tissue deformations. Because it is based on blend skinning, SMPL is compatible with existing rendering engines and we make it available for research purposes.

Google Patents [BibTex]

2016

Black, M.J., Loper, M., Mahmood, N., Pons-Moll, G., Romero, J. Skinned multi-person linear model December 2016, Application PCT/EP2016/064610 (misc)

Google Patents [BibTex]

Creating body shapes from verbal descriptions by linking similarity spaces

Hill, M. Q., Streuber, S., Hahn, C. A., Black, M. J., O’Toole, A. J.

Psychological Science, 27(11):1486-1497, November 2016, (article)

Abstract

Brief verbal descriptions of bodies (e.g. curvy, long-legged) can elicit vivid mental images. The ease with which we create these mental images belies the complexity of three-dimensional body shapes. We explored the relationship between body shapes and body descriptions and show that a small number of words can be used to generate categorically accurate representations of three-dimensional bodies. The dimensions of body shape variation that emerged in a language-based similarity space were related to major dimensions of variation computed directly from three-dimensional laser scans of 2094 bodies. This allowed us to generate three-dimensional models of people in the shape space using only their coordinates on analogous dimensions in the language-based description space. Human descriptions of photographed bodies and their corresponding models matched closely. The natural mapping between the spaces illustrates the role of language as a concise code for body shape, capturing perceptually salient global and local body features.

pdf [BibTex]

Hill, M. Q., Streuber, S., Hahn, C. A., Black, M. J., O’Toole, A. J. Creating body shapes from verbal descriptions by linking similarity spaces Psychological Science, 27(11):1486-1497, November 2016, (article)

pdf [BibTex]

Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image

Bogo, F., Kanazawa, A., Lassner, C., Gehler, P., Romero, J., Black, M. J.

In Computer Vision – ECCV 2016, pages: 561-578, Lecture Notes in Computer Science, Springer International Publishing, October 2016 (inproceedings)

Abstract

We describe the first method to automatically estimate the 3D pose of the human body as well as its 3D shape from a single unconstrained image. We estimate a full 3D mesh and show that 2D joints alone carry a surprising amount of information about body shape. The problem is challenging because of the complexity of the human body, articulation, occlusion, clothing, lighting, and the inherent ambiguity in inferring 3D from 2D. To solve this, we first use a recently published CNN-based method, DeepCut, to predict (bottom-up) the 2D body joint locations. We then fit (top-down) a recently published statistical body shape model, called SMPL, to the 2D joints. We do so by minimizing an objective function that penalizes the error between the projected 3D model joints and detected 2D joints. Because SMPL captures correlations in human shape across the population, we are able to robustly fit it to very little data. We further leverage the 3D model to prevent solutions that cause interpenetration. We evaluate our method, SMPLify, on the Leeds Sports, HumanEva, and Human3.6M datasets, showing superior pose accuracy with respect to the state of the art.

pdf Video Sup Mat video Code Project Project Page [BibTex]

Bogo, F., Kanazawa, A., Lassner, C., Gehler, P., Romero, J., Black, M. J. Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image In Computer Vision – ECCV 2016, pages: 561-578, Lecture Notes in Computer Science, Springer International Publishing, October 2016 (inproceedings)

pdf Video Sup Mat video Code Project Project Page [BibTex]

Superpixel Convolutional Networks using Bilateral Inceptions

Gadde, R., Jampani, V., Kiefel, M., Kappler, D., Gehler, P.

In European Conference on Computer Vision (ECCV), Lecture Notes in Computer Science, Springer, October 2016 (inproceedings)

Abstract

In this paper we propose a CNN architecture for semantic image segmentation. We introduce a new “bilateral inception” module that can be inserted in existing CNN architectures and performs bilateral filtering, at multiple feature-scales, between superpixels in an image. The feature spaces for bilateral filtering and other parameters of the module are learned end-to-end using standard backpropagation techniques. The bilateral inception module addresses two issues that arise with general CNN segmentation architectures. First, this module propagates information between (super) pixels while respecting image edges, thus using the structured information of the problem for improved results. Second, the layer recovers a full resolution segmentation result from the lower resolution solution of a CNN. In the experiments, we modify several existing CNN architectures by inserting our inception modules between the last CNN (1 × 1 convolution) layers. Empirical results on three different datasets show reliable improvements not only in comparison to the baseline networks, but also in comparison to several dense-pixel prediction techniques such as CRFs, while being competitive in time.

pdf supplementary poster Project Page Project Page [BibTex]

Gadde, R., Jampani, V., Kiefel, M., Kappler, D., Gehler, P. Superpixel Convolutional Networks using Bilateral Inceptions In European Conference on Computer Vision (ECCV), Lecture Notes in Computer Science, Springer, October 2016 (inproceedings)

pdf supplementary poster Project Page Project Page [BibTex]

Barrista - Caffe Well-Served

Lassner, C., Kappler, D., Kiefel, M., Gehler, P.

In ACM Multimedia Open Source Software Competition, October 2016 (inproceedings)

Abstract

The caffe framework is one of the leading deep learning toolboxes in the machine learning and computer vision community. While it offers efficiency and configurability, it falls short of a full interface to Python. With increasingly involved procedures for training deep networks and reaching depths of hundreds of layers, creating configuration files and keeping them consistent becomes an error prone process. We introduce the barrista framework, offering full, pythonic control over caffe. It separates responsibilities and offers code to solve frequently occurring tasks for pre-processing, training and model inspection. It is compatible to all caffe versions since mid 2015 and can import and export .prototxt files. Examples are included, e.g., a deep residual network implemented in only 172 lines (for arbitrary depths), comparing to 2320 lines in the official implementation for the equivalent model.

pdf link (url) DOI Project Page [BibTex]

Lassner, C., Kappler, D., Kiefel, M., Gehler, P. Barrista - Caffe Well-Served In ACM Multimedia Open Source Software Competition, October 2016 (inproceedings)

pdf link (url) DOI Project Page [BibTex]

Non-parametric Models for Structured Data and Applications to Human Bodies and Natural Scenes

Lehrmann, A.

ETH Zurich, July 2016 (phdthesis)

Abstract

The purpose of this thesis is the study of non-parametric models for structured data and their fields of application in computer vision. We aim at the development of context-sensitive architectures which are both expressive and efficient. Our focus is on directed graphical models, in particular Bayesian networks, where we combine the flexibility of non-parametric local distributions with the efficiency of a global topology with bounded treewidth. A bound on the treewidth is obtained by either constraining the maximum indegree of the underlying graph structure or by introducing determinism. The non-parametric distributions in the nodes of the graph are given by decision trees or kernel density estimators. The information flow implied by specific network topologies, especially the resultant (conditional) independencies, allows for a natural integration and control of contextual information. We distinguish between three different types of context: static, dynamic, and semantic. In four different approaches we propose models which exhibit varying combinations of these contextual properties and allow modeling of structured data in space, time, and hierarchies derived thereof. The generative character of the presented models enables a direct synthesis of plausible hypotheses. Extensive experiments validate the developed models in two application scenarios which are of particular interest in computer vision: human bodies and natural scenes. In the practical sections of this work we discuss both areas from different angles and show applications of our models to human pose, motion, and segmentation as well as object categorization and localization. Here, we benefit from the availability of modern datasets of unprecedented size and diversity. Comparisons to traditional approaches and state-of-the-art research on the basis of well-established evaluation criteria allows the objective assessment of our contributions.

pdf [BibTex]

Lehrmann, A. Non-parametric Models for Structured Data and Applications to Human Bodies and Natural Scenes ETH Zurich, July 2016 (phdthesis)

pdf [BibTex]

Dynamic baseline stereo vision-based cooperative target tracking

Ahmad, A., Ruff, E., Bülthoff, H.

19th International Conference on Information Fusion, pages: 1728-1734, July 2016 (conference)

Abstract

In this article we present a new method for multi-robot cooperative target tracking based on dynamic baseline stereo vision. The core novelty of our approach includes a computationally light-weight scheme to compute the 3D stereo measurements that exactly satisfy the epipolar constraints and a covariance intersection (CI)-based method to fuse the 3D measurements obtained by each individual robot. Using CI we are able to systematically integrate the robot localization uncertainties as well as the uncertainties in the measurements generated by the monocular camera images from each individual robot into the resulting stereo measurements. Through an extensive set of simulation and real robot results we show the robustness and accuracy of our approach with respect to ground truth. The source code related to this article is publicly accessible on our website and the datasets are available on request.

DOI [BibTex]

Ahmad, A., Ruff, E., Bülthoff, H. Dynamic baseline stereo vision-based cooperative target tracking 19th International Conference on Information Fusion, pages: 1728-1734, July 2016 (conference)

DOI [BibTex]

Body Talk: Crowdshaping Realistic 3D Avatars with Words

Streuber, S., Quiros-Ramirez, M. A., Hill, M. Q., Hahn, C. A., Zuffi, S., O’Toole, A., Black, M. J.

ACM Trans. Graph. (Proc. SIGGRAPH), 35(4):54:1-54:14, July 2016 (article)

Abstract

Realistic, metrically accurate, 3D human avatars are useful for games, shopping, virtual reality, and health applications. Such avatars are not in wide use because solutions for creating them from high-end scanners, low-cost range cameras, and tailoring measurements all have limitations. Here we propose a simple solution and show that it is surprisingly accurate. We use crowdsourcing to generate attribute ratings of 3D body shapes corresponding to standard linguistic descriptions of 3D shape. We then learn a linear function relating these ratings to 3D human shape parameters. Given an image of a new body, we again turn to the crowd for ratings of the body shape. The collection of linguistic ratings of a photograph provides remarkably strong constraints on the metric 3D shape. We call the process crowdshaping and show that our Body Talk system produces shapes that are perceptually indistinguishable from bodies created from high-resolution scans and that the metric accuracy is sufficient for many tasks. This makes body “scanning” practical without a scanner, opening up new applications including database search, visualization, and extracting avatars from books.

pdf web tool video talk (ppt) [BibTex]

Streuber, S., Quiros-Ramirez, M. A., Hill, M. Q., Hahn, C. A., Zuffi, S., O’Toole, A., Black, M. J. Body Talk: Crowdshaping Realistic 3D Avatars with Words ACM Trans. Graph. (Proc. SIGGRAPH), 35(4):54:1-54:14, July 2016 (article)

pdf web tool video talk (ppt) [BibTex]

DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation

Pishchulin, L., Insafutdinov, E., Tang, S., Andres, B., Andriluka, M., Gehler, P., Schiele, B.

In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages: 4929-4937, IEEE, June 2016 (inproceedings)

Abstract

This paper considers the task of articulated human pose estimation of multiple people in real-world images. We propose an approach that jointly solves the tasks of detection and pose estimation: it infers the number of persons in a scene, identifies occluded body parts, and disambiguates body parts between people in close proximity of each other. This joint formulation is in contrast to previous strategies, that address the problem by first detecting people and subsequently estimating their body pose. We propose a partitioning and labeling formulation of a set of body-part hypotheses generated with CNN-based part detectors. Our formulation, an instance of an integer linear program, implicitly performs non-maximum suppression on the set of part candidates and groups them to form configurations of body parts respecting geometric and appearance constraints. Experiments on four different datasets demonstrate state-of-the-art results for both single person and multi person pose estimation.

code pdf supplementary DOI Project Page [BibTex]

Pishchulin, L., Insafutdinov, E., Tang, S., Andres, B., Andriluka, M., Gehler, P., Schiele, B. DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages: 4929-4937, IEEE, June 2016 (inproceedings)

code pdf supplementary DOI Project Page [BibTex]

Video segmentation via object flow

Tsai, Y., Yang, M., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

Abstract

Video object segmentation is challenging due to fast moving objects, deforming shapes, and cluttered backgrounds. Optical flow can be used to propagate an object segmentation over time but, unfortunately, flow is often inaccurate, particularly around object boundaries. Such boundaries are precisely where we want our segmentation to be accurate. To obtain accurate segmentation across time, we propose an efficient algorithm that considers video segmentation and optical flow estimation simultaneously. For video segmentation, we formulate a principled, multiscale, spatio-temporal objective function that uses optical flow to propagate information between frames. For optical flow estimation, particularly at object boundaries, we compute the flow independently in the segmented regions and recompose the results. We call the process object flow and demonstrate the effectiveness of jointly optimizing optical flow and video segmentation using an iterative scheme. Experiments on the SegTrack v2 and Youtube-Objects datasets show that the proposed algorithm performs favorably against the other state-of-the-art methods.

pdf [BibTex]

Tsai, Y., Yang, M., Black, M. J. Video segmentation via object flow In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

pdf [BibTex]

Patches, Planes and Probabilities: A Non-local Prior for Volumetric 3D Reconstruction

Ulusoy, A. O., Black, M. J., Geiger, A.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

Abstract

In this paper, we propose a non-local structured prior for volumetric multi-view 3D reconstruction. Towards this goal, we present a novel Markov random field model based on ray potentials in which assumptions about large 3D surface patches such as planarity or Manhattan world constraints can be efficiently encoded as probabilistic priors. We further derive an inference algorithm that reasons jointly about voxels, pixels and image segments, and estimates marginal distributions of appearance, occupancy, depth, normals and planarity. Key to tractable inference is a novel hybrid representation that spans both voxel and pixel space and that integrates non-local information from 2D image segmentations in a principled way. We compare our non-local prior to commonly employed local smoothness assumptions and a variety of state-of-the-art volumetric reconstruction baselines on challenging outdoor scenes with textureless and reflective surfaces. Our experiments indicate that regularizing over larger distances has the potential to resolve ambiguities where local regularizers fail.

YouTube pdf poster suppmat Project Page [BibTex]

Ulusoy, A. O., Black, M. J., Geiger, A. Patches, Planes and Probabilities: A Non-local Prior for Volumetric 3D Reconstruction In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

YouTube pdf poster suppmat Project Page [BibTex]

Capturing Hands in Action using Discriminative Salient Points and Physics Simulation

Tzionas, D., Ballan, L., Srikantha, A., Aponte, P., Pollefeys, M., Gall, J.

International Journal of Computer Vision (IJCV), 118(2):172-193, June 2016 (article)

Abstract

Hand motion capture is a popular research field, recently gaining more attention due to the ubiquity of RGB-D sensors. However, even most recent approaches focus on the case of a single isolated hand. In this work, we focus on hands that interact with other hands or objects and present a framework that successfully captures motion in such interaction scenarios for both rigid and articulated objects. Our framework combines a generative model with discriminatively trained salient points to achieve a low tracking error and with collision detection and physics simulation to achieve physically plausible estimates even in case of occlusions and missing visual data. Since all components are unified in a single objective function which is almost everywhere differentiable, it can be optimized with standard optimization techniques. Our approach works for monocular RGB-D sequences as well as setups with multiple synchronized RGB cameras. For a qualitative and quantitative evaluation, we captured 29 sequences with a large variety of interactions and up to 150 degrees of freedom.

Website pdf link (url) DOI Project Page [BibTex]

Tzionas, D., Ballan, L., Srikantha, A., Aponte, P., Pollefeys, M., Gall, J. Capturing Hands in Action using Discriminative Salient Points and Physics Simulation International Journal of Computer Vision (IJCV), 118(2):172-193, June 2016 (article)

Website pdf link (url) DOI Project Page [BibTex]

Optical Flow with Semantic Segmentation and Localized Layers

Sevilla-Lara, L., Sun, D., Jampani, V., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3889-3898, June 2016 (inproceedings)

Abstract

Existing optical flow methods make generic, spatially homogeneous, assumptions about the spatial structure of the flow. In reality, optical flow varies across an image depending on object class. Simply put, different objects move differently. Here we exploit recent advances in static semantic scene segmentation to segment the image into objects of different types. We define different models of image motion in these regions depending on the type of object. For example, we model the motion on roads with homographies, vegetation with spatially smooth flow, and independently moving objects like cars and planes with affine motion plus deviations. We then pose the flow estimation problem using a novel formulation of localized layers, which addresses limitations of traditional layered models for dealing with complex scene motion. Our semantic flow method achieves the lowest error of any published monocular method in the KITTI-2015 flow benchmark and produces qualitatively better flow and segmentation than recent top methods on a wide range of natural videos.

video Kitti Precomputed Data (1.6GB) pdf YouTube Sequences Code Project Page Project Page [BibTex]

Sevilla-Lara, L., Sun, D., Jampani, V., Black, M. J. Optical Flow with Semantic Segmentation and Localized Layers In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3889-3898, June 2016 (inproceedings)

video Kitti Precomputed Data (1.6GB) pdf YouTube Sequences Code Project Page Project Page [BibTex]

Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks

Jampani, V., Kiefel, M., Gehler, P. V.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 4452-4461, June 2016 (inproceedings)

Abstract

Bilateral filters have wide spread use due to their edge-preserving properties. The common use case is to manually choose a parametric filter type, usually a Gaussian filter. In this paper, we will generalize the parametrization and in particular derive a gradient descent algorithm so the filter parameters can be learned from data. This derivation allows to learn high dimensional linear filters that operate in sparsely populated feature spaces. We build on the permutohedral lattice construction for efficient filtering. The ability to learn more general forms of high-dimensional filters can be used in several diverse applications. First, we demonstrate the use in applications where single filter applications are desired for runtime reasons. Further, we show how this algorithm can be used to learn the pairwise potentials in densely connected conditional random fields and apply these to different image segmentation tasks. Finally, we introduce layers of bilateral filters in CNNs and propose bilateral neural networks for the use of high-dimensional sparse data. This view provides new ways to encode model structure into network architectures. A diverse set of experiments empirically validates the usage of general forms of filters.

project page code CVF open-access pdf supplementary poster Project Page Project Page [BibTex]

Jampani, V., Kiefel, M., Gehler, P. V. Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 4452-4461, June 2016 (inproceedings)

project page code CVF open-access pdf supplementary poster Project Page Project Page [BibTex]

Occlusion boundary detection via deep exploration of context

Fu, H., Wang, C., Tao, D., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

Abstract

Occlusion boundaries contain rich perceptual information about the underlying scene structure. They also provide important cues in many visual perception tasks such as scene understanding, object recognition, and segmentation. In this paper, we improve occlusion boundary detection via enhanced exploration of contextual information (e.g., local structural boundary patterns, observations from surrounding regions, and temporal context), and in doing so develop a novel approach based on convolutional neural networks (CNNs) and conditional random fields (CRFs). Experimental results demonstrate that our detector significantly outperforms the state-of-the-art (e.g., improving the F-measure from 0.62 to 0.71 on the commonly used CMU benchmark). Last but not least, we empirically assess the roles of several important components of the proposed detector, so as to validate the rationale behind this approach.

pdf [BibTex]

Fu, H., Wang, C., Tao, D., Black, M. J. Occlusion boundary detection via deep exploration of context In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

pdf [BibTex]

Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer

Xie, J., Kiefel, M., Sun, M., Geiger, A.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

Abstract

Semantic annotations are vital for training models for object recognition, semantic segmentation or scene understanding. Unfortunately, pixelwise annotation of images at very large scale is labor-intensive and only little labeled data is available, particularly at instance level and for street scenes. In this paper, we propose to tackle this problem by lifting the semantic instance labeling task from 2D into 3D. Given reconstructions from stereo or laser data, we annotate static 3D scene elements with rough bounding primitives and develop a probabilistic model which transfers this information into the image domain. We leverage our method to obtain 2D labels for a novel suburban video dataset which we have collected, resulting in 400k semantic and instance image annotations. A comparison of our method to state-of-the-art label transfer baselines reveals that 3D information enables more efficient annotation while at the same time resulting in improved accuracy and time-coherent labels.

pdf suppmat Project Page Project Page [BibTex]

Xie, J., Kiefel, M., Sun, M., Geiger, A. Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)

pdf suppmat Project Page Project Page [BibTex]

Appealing female avatars from 3D body scans: Perceptual effects of stylization

Fleming, R., Mohler, B., Romero, J., Black, M. J., Breidt, M.

In 11th Int. Conf. on Computer Graphics Theory and Applications (GRAPP), Febuary 2016 (inproceedings)

Abstract

Advances in 3D scanning technology allow us to create realistic virtual avatars from full body 3D scan data. However, negative reactions to some realistic computer generated humans suggest that this approach might not always provide the most appealing results. Using styles derived from existing popular character designs, we present a novel automatic stylization technique for body shape and colour information based on a statistical 3D model of human bodies. We investigate whether such stylized body shapes result in increased perceived appeal with two different experiments: One focuses on body shape alone, the other investigates the additional role of surface colour and lighting. Our results consistently show that the most appealing avatar is a partially stylized one. Importantly, avatars with high stylization or no stylization at all were rated to have the least appeal. The inclusion of colour information and improvements to render quality had no significant effect on the overall perceived appeal of the avatars, and we observe that the body shape primarily drives the change in appeal ratings. For body scans with colour information, we found that a partially stylized avatar was most effective, increasing average appeal ratings by approximately 34%.

pdf Project Page [BibTex]

Fleming, R., Mohler, B., Romero, J., Black, M. J., Breidt, M. Appealing female avatars from 3D body scans: Perceptual effects of stylization In 11th Int. Conf. on Computer Graphics Theory and Applications (GRAPP), Febuary 2016 (inproceedings)

pdf Project Page [BibTex]

Human Pose Estimation from Video and IMUs

Marcard, T. V., Pons-Moll, G., Rosenhahn, B.

Transactions on Pattern Analysis and Machine Intelligence PAMI, 38(8):1533-1547, January 2016 (article)

data pdf dataset_documentation [BibTex]

Marcard, T. V., Pons-Moll, G., Rosenhahn, B. Human Pose Estimation from Video and IMUs Transactions on Pattern Analysis and Machine Intelligence PAMI, 38(8):1533-1547, January 2016 (article)

data pdf dataset_documentation [BibTex]

Deep Discrete Flow

Güney, F., Geiger, A.

Asian Conference on Computer Vision (ACCV), 2016 (conference) Accepted

pdf suppmat Project Page [BibTex]

Güney, F., Geiger, A. Deep Discrete Flow Asian Conference on Computer Vision (ACCV), 2016 (conference) Accepted

pdf suppmat Project Page [BibTex]

Moving-horizon Nonlinear Least Squares-based Multirobot Cooperative Perception

Ahmad, A., Bülthoff, H.

Robotics and Autonomous Systems, 83, pages: 275-286, 2016 (article)

Abstract

In this article we present an online estimator for multirobot cooperative localization and target tracking based on nonlinear least squares minimization. Our method not only makes the rigorous optimization-based approach applicable online but also allows the estimator to be stable and convergent. We do so by employing a moving horizon technique to nonlinear least squares minimization and a novel design of the arrival cost function that ensures stability and convergence of the estimator. Through an extensive set of real robot experiments, we demonstrate the robustness of our method as well as the optimality of the arrival cost function. The experiments include comparisons of our method with i) an extended Kalman filter-based online-estimator and ii) an offline-estimator based on full-trajectory nonlinear least squares.

DOI Project Page [BibTex]

Ahmad, A., Bülthoff, H. Moving-horizon Nonlinear Least Squares-based Multirobot Cooperative Perception Robotics and Autonomous Systems, 83, pages: 275-286, 2016 (article)

DOI Project Page [BibTex]

Perceiving Systems (2011-2015)

Scientific Advisory Board Report, 2016 (misc)

pdf [BibTex]

Perceiving Systems (2011-2015) Scientific Advisory Board Report, 2016 (misc)

pdf [BibTex]

Shape estimation of subcutaneous adipose tissue using an articulated statistical shape model

Yeo, S. Y., Romero, J., Loper, M., Machann, J., Black, M.

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 0(0):1-8, 2016 (article)

publisher website preprint pdf link (url) DOI Project Page [BibTex]

Yeo, S. Y., Romero, J., Loper, M., Machann, J., Black, M. Shape estimation of subcutaneous adipose tissue using an articulated statistical shape model Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 0(0):1-8, 2016 (article)

publisher website preprint pdf link (url) DOI Project Page [BibTex]

Multi-Person Tracking by Multicuts and Deep Matching

(Winner of the Multi-Object Tracking Challenge ECCV 2016)

Tang, S., Andres, B., Andriluka, M., Schiele, B.

ECCV Workshop on Benchmarking Mutliple Object Tracking, 2016 (conference)

PDF [BibTex]

Tang, S., Andres, B., Andriluka, M., Schiele, B. Multi-Person Tracking by Multicuts and Deep Matching ECCV Workshop on Benchmarking Mutliple Object Tracking, 2016 (conference)

PDF [BibTex]

Reconstructing Articulated Rigged Models from RGB-D Videos

Tzionas, D., Gall, J.

In European Conference on Computer Vision Workshops 2016 (ECCVW’16) - Workshop on Recovering 6D Object Pose (R6D’16), pages: 620-633, Springer International Publishing, 2016 (inproceedings)

Abstract

Although commercial and open-source software exist to reconstruct a static object from a sequence recorded with an RGB-D sensor, there is a lack of tools that build rigged models of articulated objects that deform realistically and can be used for tracking or animation. In this work, we fill this gap and propose a method that creates a fully rigged model of an articulated object from depth data of a single sensor. To this end, we combine deformable mesh tracking, motion segmentation based on spectral clustering and skeletonization based on mean curvature flow. The fully rigged model then consists of a watertight mesh, embedded skeleton, and skinning weights.

pdf suppl Project's Website YouTube link (url) DOI [BibTex]

Tzionas, D., Gall, J. Reconstructing Articulated Rigged Models from RGB-D Videos In European Conference on Computer Vision Workshops 2016 (ECCVW’16) - Workshop on Recovering 6D Object Pose (R6D’16), pages: 620-633, Springer International Publishing, 2016 (inproceedings)

pdf suppl Project's Website YouTube link (url) DOI [BibTex]

A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects

Keuper, M., Tang, S., Yu, Z., Andres, B., Brox, T., Schiele, B.

In arXiv:1607.06317, 2016 (inproceedings)

PDF [BibTex]

Keuper, M., Tang, S., Yu, Z., Andres, B., Brox, T., Schiele, B. A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects In arXiv:1607.06317, 2016 (inproceedings)

PDF [BibTex]

The GRASP Taxonomy of Human Grasp Types

Feix, T., Romero, J., Schmiedmayer, H., Dollar, A., Kragic, D.

Human-Machine Systems, IEEE Transactions on, 46(1):66-77, 2016 (article)

publisher website pdf DOI Project Page [BibTex]

Feix, T., Romero, J., Schmiedmayer, H., Dollar, A., Kragic, D. The GRASP Taxonomy of Human Grasp Types Human-Machine Systems, IEEE Transactions on, 46(1):66-77, 2016 (article)

publisher website pdf DOI Project Page [BibTex]

Map-Based Probabilistic Visual Self-Localization

Brubaker, M. A., Geiger, A., Urtasun, R.

IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2016 (article)

Abstract

Accurate and efficient self-localization is a critical problem for autonomous systems. This paper describes an affordable solution to vehicle self-localization which uses odometry computed from two video cameras and road maps as the sole inputs. The core of the method is a probabilistic model for which an efficient approximate inference algorithm is derived. The inference algorithm is able to utilize distributed computation in order to meet the real-time requirements of autonomous systems in some instances. Because of the probabilistic nature of the model the method is capable of coping with various sources of uncertainty including noise in the visual odometry and inherent ambiguities in the map (e.g., in a Manhattan world). By exploiting freely available, community developed maps and visual odometry measurements, the proposed method is able to localize a vehicle to 4m on average after 52 seconds of driving on maps which contain more than 2,150km of drivable roads.

pdf Project Page [BibTex]

Brubaker, M. A., Geiger, A., Urtasun, R. Map-Based Probabilistic Visual Self-Localization IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2016 (article)

pdf Project Page [BibTex]

2011

High-quality reflection separation using polarized images

Kong, N., Tai, Y., Shin, S. Y.

IEEE Transactions on Image Processing, 20(12):3393-3405, IEEE Signal Processing Society, December 2011 (article)

Abstract

In this paper, we deal with a problem of separating the effect of reflection from images captured behind glass. The input consists of multiple polarized images captured from the same view point but with different polarizer angles. The output is the high quality separation of the reflection layer and the background layer from the images. We formulate this problem as a constrained optimization problem and propose a framework that allows us to fully exploit the mutually exclusive image information in our input data. We test our approach on various images and demonstrate that our approach can generate good reflection separation results.

Publisher site [BibTex]

2011

Kong, N., Tai, Y., Shin, S. Y. High-quality reflection separation using polarized images IEEE Transactions on Image Processing, 20(12):3393-3405, IEEE Signal Processing Society, December 2011 (article)

Publisher site [BibTex]

Outdoor Human Motion Capture using Inverse Kinematics and von Mises-Fisher Sampling

Pons-Moll, G., Baak, A., Gall, J., Leal-Taixe, L., Mueller, M., Seidel, H., Rosenhahn, B.

In IEEE International Conference on Computer Vision (ICCV), pages: 1243-1250, November 2011 (inproceedings)

project page pdf supplemental [BibTex]

Pons-Moll, G., Baak, A., Gall, J., Leal-Taixe, L., Mueller, M., Seidel, H., Rosenhahn, B. Outdoor Human Motion Capture using Inverse Kinematics and von Mises-Fisher Sampling In IEEE International Conference on Computer Vision (ICCV), pages: 1243-1250, November 2011 (inproceedings)

project page pdf supplemental [BibTex]

Home 3D body scans from noisy image and range data

Weiss, A., Hirshberg, D., Black, M.

In Int. Conf. on Computer Vision (ICCV), pages: 1951-1958, IEEE, Barcelona, November 2011 (inproceedings)

Abstract

The 3D shape of the human body is useful for applications in fitness, games and apparel. Accurate body scanners, however, are expensive, limiting the availability of 3D body models. We present a method for human shape reconstruction from noisy monocular image and range data using a single inexpensive commodity sensor. The approach combines low-resolution image silhouettes with coarse range data to estimate a parametric model of the body. Accurate 3D shape estimates are obtained by combining multiple monocular views of a person moving in front of the sensor. To cope with varying body pose, we use a SCAPE body model which factors 3D body shape and pose variations. This enables the estimation of a single consistent shape while allowing pose to vary. Additionally, we describe a novel method to minimize the distance between the projected 3D body contour and the image silhouette that uses analytic derivatives of the objective function. We propose a simple method to estimate standard body measurements from the recovered SCAPE model and show that the accuracy of our method is competitive with commercial body scanning systems costing orders of magnitude more.

pdf YouTube poster Project Page Project Page [BibTex]

Weiss, A., Hirshberg, D., Black, M. Home 3D body scans from noisy image and range data In Int. Conf. on Computer Vision (ICCV), pages: 1951-1958, IEEE, Barcelona, November 2011 (inproceedings)

pdf YouTube poster Project Page Project Page [BibTex]

Means in spaces of tree-like shapes

Aasa Feragen, Soren Hauberg, Mads Nielsen, Francois Lauze

In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 736 -746, IEEE, november 2011 (inproceedings)

Publishers site PDF Suppl. material [BibTex]

Aasa Feragen, Soren Hauberg, Mads Nielsen, Francois Lauze Means in spaces of tree-like shapes In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 736 -746, IEEE, november 2011 (inproceedings)

Publishers site PDF Suppl. material [BibTex]

Everybody needs somebody: modeling social and grouping behavior on a linear programming multiple people tracker

Leal-Taixé, L., Rosenhahn, G. P. A. B.

In IEEE International Conference on Computer Vision Workshops (IICCVW), November 2011 (inproceedings)

project page pdf [BibTex]

Leal-Taixé, L., Rosenhahn, G. P. A. B. Everybody needs somebody: modeling social and grouping behavior on a linear programming multiple people tracker In IEEE International Conference on Computer Vision Workshops (IICCVW), November 2011 (inproceedings)

project page pdf [BibTex]

Evaluating the Automated Alignment of 3D Human Body Scans

Hirshberg, D. A., Loper, M., Rachlin, E., Tsoli, A., Weiss, A., Corner, B., Black, M. J.

In 2nd International Conference on 3D Body Scanning Technologies, pages: 76-86, (Editors: D’Apuzzo, Nicola), Hometrica Consulting, Lugano, Switzerland, October 2011 (inproceedings)

Abstract

The statistical analysis of large corpora of human body scans requires that these scans be in alignment, either for a small set of key landmarks or densely for all the vertices in the scan. Existing techniques tend to rely on hand-placed landmarks or algorithms that extract landmarks from scans. The former is time consuming and subjective while the latter is error prone. Here we show that a model-based approach can align meshes automatically, producing alignment accuracy similar to that of previous methods that rely on many landmarks. Specifically, we align a low-resolution, artist-created template body mesh to many high-resolution laser scans. Our alignment procedure employs a robust iterative closest point method with a regularization that promotes smooth and locally rigid deformation of the template mesh. We evaluate our approach on 50 female body models from the CAESAR dataset that vary significantly in body shape. To make the method fully automatic, we define simple feature detectors for the head and ankles, which provide initial landmark locations. We find that, if body poses are fairly similar, as in CAESAR, the fully automated method provides dense alignments that enable statistical analysis and anthropometric measurement.

pdf slides DOI Project Page [BibTex]

Hirshberg, D. A., Loper, M., Rachlin, E., Tsoli, A., Weiss, A., Corner, B., Black, M. J. Evaluating the Automated Alignment of 3D Human Body Scans In 2nd International Conference on 3D Body Scanning Technologies, pages: 76-86, (Editors: D’Apuzzo, Nicola), Hometrica Consulting, Lugano, Switzerland, October 2011 (inproceedings)

pdf slides DOI Project Page [BibTex]

Branch&Rank: Non-Linear Object Detection

(Best Impact Paper Prize)

Lehmann, A., Gehler, P., VanGool, L.

In Proceedings of the British Machine Vision Conference (BMVC), pages: 8.1-8.11, (Editors: Jesse Hoey and Stephen McKenna and Emanuele Trucco), BMVA Press, September 2011, http://dx.doi.org/10.5244/C.25.8 (inproceedings)

video of talk pdf slides supplementary [BibTex]

Lehmann, A., Gehler, P., VanGool, L. Branch&Rank: Non-Linear Object Detection In Proceedings of the British Machine Vision Conference (BMVC), pages: 8.1-8.11, (Editors: Jesse Hoey and Stephen McKenna and Emanuele Trucco), BMVA Press, September 2011, http://dx.doi.org/10.5244/C.25.8 (inproceedings)

video of talk pdf slides supplementary [BibTex]

A human inspired gaze estimation system

Wulff, J., Sinha, P.

Journal of Vision, 11(11):507-507, ARVO, September 2011 (article)

Abstract

Estimating another person's gaze is a crucial skill in human social interactions. The social component is most apparent in dyadic gaze situations, in which the looker seems to look into the eyes of the observer, thereby signaling interest or a turn to speak. In a triadic situation, on the other hand, the looker's gaze is averted from the observer and directed towards another, specific target. This is mostly interpreted as a cue for joint attention, creating awareness of a predator or another point of interest. In keeping with the task's social significance, humans are very proficient at gaze estimation. Our accuracy ranges from less than one degree for dyadic settings to approximately 2.5 degrees for triadic ones. Our goal in this work is to draw inspiration from human gaze estimation mechanisms in order to create an artificial system that can approach the former's accuracy levels. Since human performance is severely impaired by both image-based degradations (Ando, 2004) and a change of facial configurations (Jenkins & Langton, 2003), the underlying principles are believed to be based both on simple image cues such as contrast/brightness distribution and on more complex geometric processing to reconstruct the actual shape of the head. By incorporating both kinds of cues in our system's design, we are able to surpass the accuracy of existing eye-tracking systems, which rely exclusively on either image-based or geometry-based cues (Yamazoe et al., 2008). A side-benefit of this combined approach is that it allows for gaze estimation despite moderate view-point changes. This is important for settings where subjects, say young children or certain kinds of patients, might not be fully cooperative to allow a careful calibration. Our model and implementation of gaze estimation opens up new experimental questions about human mechanisms while also providing a useful tool for general calibration-free, non-intrusive remote eye-tracking.

link (url) DOI [BibTex]

Wulff, J., Sinha, P. A human inspired gaze estimation system Journal of Vision, 11(11):507-507, ARVO, September 2011 (article)

link (url) DOI [BibTex]

Detecting synchrony in degraded audio-visual streams

Dhandhania, K., Wulff, J., Sinha, P.

Journal of Vision, 11(11):800-800, ARVO, September 2011 (article)

Abstract

Even 8–10 week old infants, when presented with two dynamic faces and a speech stream, look significantly longer at the ‘correct’ talking person (Patterson & Werker, 2003). This is true even though their reduced visual acuity prevents them from utilizing high spatial frequencies. Computational analyses in the field of audio/video synchrony and automatic speaker detection (e.g. Hershey & Movellan, 2000), in contrast, usually depend on high-resolution images. Therefore, the correlation mechanisms found in these computational studies are not directly applicable to the processes through which we learn to integrate the modalities of speech and vision. In this work, we investigated the correlation between speech signals and degraded video signals. We found a high correlation persisting even with high image degradation, resembling the low visual acuity of young infants. Additionally (in a fashion similar to Graf et al., 2002) we explored which parts of the face correlate with the audio in the degraded video sequences. Perfect synchrony and small offsets in the audio were used while finding the correlation, thereby detecting visual events preceding and following audio events. In order to achieve a sufficiently high temporal resolution, high-speed video sequences (500 frames per second) of talking people were used. This is a temporal resolution unachieved in previous studies and has allowed us to capture very subtle and short visual events. We believe that the results of this study might be interesting not only to vision researchers, but, by revealing subtle effects on a very fine timescale, also to people working in computer graphics and the generation and animation of artificial faces.

link (url) DOI [BibTex]

Dhandhania, K., Wulff, J., Sinha, P. Detecting synchrony in degraded audio-visual streams Journal of Vision, 11(11):800-800, ARVO, September 2011 (article)

link (url) DOI [BibTex]

Efficient and Robust Shape Matching for Model Based Human Motion Capture

Pons-Moll, G., Leal-Taixé, L., Truong, T., Rosenhahn, B.

In German Conference on Pattern Recognition (GCPR), pages: 416-425, September 2011 (inproceedings)

project page pdf [BibTex]

Pons-Moll, G., Leal-Taixé, L., Truong, T., Rosenhahn, B. Efficient and Robust Shape Matching for Model Based Human Motion Capture In German Conference on Pattern Recognition (GCPR), pages: 416-425, September 2011 (inproceedings)

project page pdf [BibTex]

BrainGate pilot clinical trials: Progress in translating neural engineering principles to clinical testing

33rd Annual International IEEE EMBS Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, August 2011 (conference)

[BibTex]

Hochberg, L., Simeral, J., Black, M., Bacher, D., Barefoot, L., Berhanu, E., Borton, D., Cash, S., Feldman, J., Gallivan, E., Homer, M., Jarosiewicz, B., King, B., Liu, J., Malik, W., Masse, N., Perge, J., Rosler, D., Schmansky, N., Travers, B., Truccolo, W., Nurmikko, A., Donoghue, J. BrainGate pilot clinical trials: Progress in translating neural engineering principles to clinical testing 33rd Annual International IEEE EMBS Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, August 2011 (conference)

[BibTex]

ISocRob-MSL 2011 Team Description Paper for Middle Sized League

Messias, J., Ahmad, A., Reis, J., Sousa, J., Lima, P.

15th Annual RoboCup International Symposium 2011, July 2011 (techreport)

Abstract

This paper describes the status of the ISocRob MSL robotic soccer team as required by the RoboCup 2011 qualification procedures. The most relevant technical and scientifical developments carried out by the team, since its last participation in the RoboCup MSL competitions, are here detailed. These include cooperative localization, cooperative object tracking, planning under uncertainty, obstacle detection and improvements to self-localization.

link (url) [BibTex]

Messias, J., Ahmad, A., Reis, J., Sousa, J., Lima, P. ISocRob-MSL 2011 Team Description Paper for Middle Sized League 15th Annual RoboCup International Symposium 2011, July 2011 (techreport)

link (url) [BibTex]

Trajectory Space: A Dual Representation for Nonrigid Structure from Motion

Akhter, I., Sheikh, Y., Khan, S., Kanade, T.

Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33(7):1442-1456, IEEE, July 2011 (article)

Abstract

Existing approaches to nonrigid structure from motion assume that the instantaneous 3D shape of a deforming object is a linear combination of basis shapes. These basis are object dependent and therefore have to be estimated anew for each video sequence. In contrast, we propose a dual approach to describe the evolving 3D structure in trajectory space by a linear combination of basis trajectories. We describe the dual relationship between the two approaches, showing that they both have equal power for representing 3D structure. We further show that the temporal smoothness in 3D trajectories alone can be used for recovering nonrigid structure from a moving camera. The principal advantage of expressing deforming 3D structure in trajectory space is that we can define an object independent basis. This results in a significant reduction in unknowns, and corresponding stability in estimation. We propose the use of the Discrete Cosine Transform (DCT) as the object independent basis and empirically demonstrate that it approaches Principal Component Analysis (PCA) for natural motions. We report the performance of the proposed method, quantitatively using motion capture data, and qualitatively on several video sequences exhibiting nonrigid motions including piecewise rigid motion, partially nonrigid motion (such as a facial expressions), and highly nonrigid motion (such as a person walking or dancing).

pdf project page [BibTex]

Akhter, I., Sheikh, Y., Khan, S., Kanade, T. Trajectory Space: A Dual Representation for Nonrigid Structure from Motion Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33(7):1442-1456, IEEE, July 2011 (article)

pdf project page [BibTex]

Learning Output Kernels with Block Coordinate Descent

Dinuzzo, F., Ong, C. S., Gehler, P., Pillonetto, G.

In Proceedings of the 28th International Conference on Machine Learning (ICML-11), pages: 49-56, ICML ’11, (Editors: Getoor, Lise and Scheffer, Tobias), ACM, New York, NY, USA, June 2011 (inproceedings)

data+code pdf [BibTex]

Dinuzzo, F., Ong, C. S., Gehler, P., Pillonetto, G. Learning Output Kernels with Block Coordinate Descent In Proceedings of the 28th International Conference on Machine Learning (ICML-11), pages: 49-56, ICML ’11, (Editors: Getoor, Lise and Scheffer, Tobias), ACM, New York, NY, USA, June 2011 (inproceedings)

data+code pdf [BibTex]

Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief Propagation

Sigal, L., Isard, M., Haussecker, H., Black, M. J.

International Journal of Computer Vision, 98(1):15-48, Springer Netherlands, May 2011 (article)

Abstract

We formulate the problem of 3D human pose estimation and tracking as one of inference in a graphical model. Unlike traditional kinematic tree representations, our model of the body is a collection of loosely-connected body-parts. In particular, we model the body using an undirected graphical model in which nodes correspond to parts and edges to kinematic, penetration, and temporal constraints imposed by the joints and the world. These constraints are encoded using pair-wise statistical distributions, that are learned from motion-capture training data. Human pose and motion estimation is formulated as inference in this graphical model and is solved using Particle Message Passing (PaMPas). PaMPas is a form of non-parametric belief propagation that uses a variation of particle filtering that can be applied over a general graphical model with loops. The loose-limbed model and decentralized graph structure allow us to incorporate information from "bottom-up" visual cues, such as limb and head detectors, into the inference process. These detectors enable automatic initialization and aid recovery from transient tracking failures. We illustrate the method by automatically tracking people in multi-view imagery using a set of calibrated cameras and present quantitative evaluation using the HumanEva dataset.

pdf publisher's site link (url) Project Page Project Page [BibTex]

Sigal, L., Isard, M., Haussecker, H., Black, M. J. Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief Propagation International Journal of Computer Vision, 98(1):15-48, Springer Netherlands, May 2011 (article)

pdf publisher's site link (url) Project Page Project Page [BibTex]

Point-and-Click Cursor Control With an Intracortical Neural Interface System by Humans With Tetraplegia

Kim, S., Simeral, J. D., Hochberg, L. R., Donoghue, J. P., Friehs, G. M., Black, M. J.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 19(2):193-203, April 2011 (article)

Abstract

We present a point-and-click intracortical neural interface system (NIS) that enables humans with tetraplegia to volitionally move a 2D computer cursor in any desired direction on a computer screen, hold it still and click on the area of interest. This direct brain-computer interface extracts both discrete (click) and continuous (cursor velocity) signals from a single small population of neurons in human motor cortex. A key component of this system is a multi-state probabilistic decoding algorithm that simultaneously decodes neural spiking activity and outputs either a click signal or the velocity of the cursor. The algorithm combines a linear classifier, which determines whether the user is intending to click or move the cursor, with a Kalman filter that translates the neural population activity into cursor velocity. We present a paradigm for training the multi-state decoding algorithm using neural activity observed during imagined actions. Two human participants with tetraplegia (paralysis of the four limbs) performed a closed-loop radial target acquisition task using the point-and-click NIS over multiple sessions. We quantified point-and-click performance using various human-computer interaction measurements for pointing devices. We found that participants were able to control the cursor motion accurately and click on specified targets with a small error rate (< 3% in one participant). This study suggests that signals from a small ensemble of motor cortical neurons (~40) can be used for natural point-and-click 2D cursor control of a personal computer.

pdf publishers's site pub med link (url) Project Page [BibTex]

Kim, S., Simeral, J. D., Hochberg, L. R., Donoghue, J. P., Friehs, G. M., Black, M. J. Point-and-Click Cursor Control With an Intracortical Neural Interface System by Humans With Tetraplegia IEEE Transactions on Neural Systems and Rehabilitation Engineering, 19(2):193-203, April 2011 (article)

pdf publishers's site pub med link (url) Project Page [BibTex]

A Database and Evaluation Methodology for Optical Flow

Baker, S., Scharstein, D., Lewis, J. P., Roth, S., Black, M. J., Szeliski, R.

International Journal of Computer Vision, 92(1):1-31, March 2011 (article)

Abstract

The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance. The challenges for optical flow algorithms today go beyond the datasets and evaluation methods proposed in that paper. Instead, they center on problems associated with complex natural scenes, including nonrigid motion, real sensor noise, and motion discontinuities. We propose a new set of benchmarks and evaluation methods for the next generation of optical flow algorithms. To that end, we contribute four types of data to test different aspects of optical flow algorithms: (1) sequences with nonrigid motion where the ground-truth flow is determined by tracking hidden fluorescent texture, (2) realistic synthetic sequences, (3) high frame-rate video used to study interpolation error, and (4) modified stereo sequences of static scenes. In addition to the average angular error used by Barron et al., we compute the absolute flow endpoint error, measures for frame interpolation error, improved statistics, and results at motion discontinuities and in textureless regions. In October 2007, we published the performance of several well-known methods on a preliminary version of our data to establish the current state of the art. We also made the data freely available on the web at http://vision.middlebury.edu/flow/ . Subsequently a number of researchers have uploaded their results to our website and published papers using the data. A significant improvement in performance has already been achieved. In this paper we analyze the results obtained to date and draw a large number of conclusions from them.

pdf pdf from publisher Middlebury Flow Evaluation Website [BibTex]

Baker, S., Scharstein, D., Lewis, J. P., Roth, S., Black, M. J., Szeliski, R. A Database and Evaluation Methodology for Optical Flow International Journal of Computer Vision, 92(1):1-31, March 2011 (article)

pdf pdf from publisher Middlebury Flow Evaluation Website [BibTex]

Role of expertise and contralateral symmetry in the diagnosis of pneumoconiosis: an experimental study

Jampani, V., Vaidya, V., Sivaswamy, J., Tourani, K. L.

In Proc. SPIE 7966, Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, 2011, Florida, March 2011 (inproceedings)

Abstract

Pneumoconiosis, a lung disease caused by the inhalation of dust, is mainly diagnosed using chest radiographs. The effects of using contralateral symmetric (CS) information present in chest radiographs in the diagnosis of pneumoconiosis are studied using an eye tracking experimental study. The role of expertise and the influence of CS information on the performance of readers with different expertise level are also of interest. Experimental subjects ranging from novices & medical students to staff radiologists were presented with 17 double and 16 single lung images, and were asked to give profusion ratings for each lung zone. Eye movements and the time for their diagnosis were also recorded. Kruskal-Wallis test (χ2(6) = 13.38, p = .038), showed that the observer error (average sum of absolute differences) in double lung images differed significantly across the different expertise categories when considering all the participants. Wilcoxon-signed rank test indicated that the observer error was significantly higher for single-lung images (Z = 3.13, p < .001) than for the double-lung images for all the participants. Mann-Whitney test (U = 28, p = .038) showed that the differential error between single and double lung images is significantly higher in doctors [staff & residents] than in non-doctors [others]. Thus, Expertise & CS information plays a significant role in the diagnosis of pneumoconiosis. CS information helps in diagnosing pneumoconiosis by reducing the general tendency of giving less profusion ratings. Training and experience appear to play important roles in learning to use the CS information present in the chest radiographs.

url link (url) [BibTex]

Jampani, V., Vaidya, V., Sivaswamy, J., Tourani, K. L. Role of expertise and contralateral symmetry in the diagnosis of pneumoconiosis: an experimental study In Proc. SPIE 7966, Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, 2011, Florida, March 2011 (inproceedings)

url link (url) [BibTex]

Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance

Gehler, P., Rother, C., Kiefel, M., Zhang, L., Schölkopf, B.

In Advances in Neural Information Processing Systems 24, pages: 765-773, (Editors: Shawe-Taylor, John and Zemel, Richard S. and Bartlett, Peter L. and Pereira, Fernando C. N. and Weinberger, Kilian Q.), Curran Associates, Inc., Red Hook, NY, USA, 2011 (inproceedings)

Abstract

We address the challenging task of decoupling material properties from lighting properties given a single image. In the last two decades virtually all works have concentrated on exploiting edge information to address this problem. We take a different route by introducing a new prior on reflectance, that models reflectance values as being drawn from a sparse set of basis colors. This results in a Random Field model with global, latent variables (basis colors) and pixel-accurate output reflectance values. We show that without edge information high-quality results can be achieved, that are on par with methods exploiting this source of information. Finally, we are able to improve on state-of-the-art results by integrating edge information into our model. We believe that our new approach is an excellent starting point for future developments in this field.

website + code pdf poster Project Page Project Page [BibTex]

Gehler, P., Rother, C., Kiefel, M., Zhang, L., Schölkopf, B. Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance In Advances in Neural Information Processing Systems 24, pages: 765-773, (Editors: Shawe-Taylor, John and Zemel, Richard S. and Bartlett, Peter L. and Pereira, Fernando C. N. and Weinberger, Kilian Q.), Curran Associates, Inc., Red Hook, NY, USA, 2011 (inproceedings)

website + code pdf poster Project Page Project Page [BibTex]

OpenBioSafetyLab: A virtual world based biosafety training application for medical students

Nakasone, A., Tang, S., Shigematsu, M., Heinecke, B., Fujimoto, S., Prendinger, H.

In International Conference on Information Technology: New Generations (ITNG), IEEE CPS, 2011 (inproceedings)

PDF [BibTex]

Nakasone, A., Tang, S., Shigematsu, M., Heinecke, B., Fujimoto, S., Prendinger, H. OpenBioSafetyLab: A virtual world based biosafety training application for medical students In International Conference on Information Technology: New Generations (ITNG), IEEE CPS, 2011 (inproceedings)

PDF [BibTex]

Combining wireless neural recording and video capture for the analysis of natural gait

Foster, J., Freifeld, O., Nuyujukian, P., Ryu, S., Black, M. J., Shenoy, K.

In Proc. 5th Int. IEEE EMBS Conf. on Neural Engineering, pages: 613-616, IEEE, 2011 (inproceedings)

pdf Project Page [BibTex]

Foster, J., Freifeld, O., Nuyujukian, P., Ryu, S., Black, M. J., Shenoy, K. Combining wireless neural recording and video capture for the analysis of natural gait In Proc. 5th Int. IEEE EMBS Conf. on Neural Engineering, pages: 613-616, IEEE, 2011 (inproceedings)

pdf Project Page [BibTex]

Tagged Cardiac MR Image Segmentation Using Boundary & Regional-Support and Graph-based Deformable Priors

Xiang, B., Wang, C., Deux, J., Rahmouni, A., Paragios, N.

In IEEE International Symposium on Biomedical Imaging (ISBI), 2011 (inproceedings)

pdf [BibTex]

Xiang, B., Wang, C., Deux, J., Rahmouni, A., Paragios, N. Tagged Cardiac MR Image Segmentation Using Boundary & Regional-Support and Graph-based Deformable Priors In IEEE International Symposium on Biomedical Imaging (ISBI), 2011 (inproceedings)

pdf [BibTex]

Multiview Structure from Motion in Trajectory Space

Zaheer, A., Akhter, I., Mohammad, H. B., Marzban, S., Khan, S.

In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 2447-2453, 2011 (inproceedings)

Abstract

Most nonrigid objects exhibit temporal regularities in their deformations. Recently it was proposed that these regularities can be parameterized by assuming that the non- rigid structure lies in a small dimensional trajectory space. In this paper, we propose a factorization approach for 3D reconstruction from multiple static cameras under the com- pact trajectory subspace representation. Proposed factor- ization is analogous to rank-3 factorization of rigid struc- ture from motion problem, in transformed space. The benefit of our approach is that the 3D trajectory basis can be directly learned from the image observations. This also allows us to impute missing observations and denoise tracking errors without explicit estimation of the 3D structure. In contrast to standard triangulation based methods which require points to be visible in at least two cameras, our ap- proach can reconstruct points, which remain occluded even in all the cameras for quite a long time. This makes our solution especially suitable for occlusion handling in motion capture systems. We demonstrate robustness of our method on challenging real and synthetic scenarios.

pdf project page [BibTex]

Zaheer, A., Akhter, I., Mohammad, H. B., Marzban, S., Khan, S. Multiview Structure from Motion in Trajectory Space In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 2447-2453, 2011 (inproceedings)

pdf project page [BibTex]

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