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42 results (View BibTeX file of all listed publications)

2016

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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 fi rst 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 fi t 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]

2016

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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

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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]

2007

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A Database and Evaluation Methodology for Optical Flow

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

In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

pdf [BibTex]

2007

Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R. A Database and Evaluation Methodology for Optical Flow In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

pdf [BibTex]

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Shining a light on human pose: On shadows, shading and the estimation of pose and shape,

Balan, A., Black, M. J., Haussecker, H., Sigal, L.

In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

pdf YouTube [BibTex]

Balan, A., Black, M. J., Haussecker, H., Sigal, L. Shining a light on human pose: On shadows, shading and the estimation of pose and shape, In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

pdf YouTube [BibTex]

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Ensemble spiking activity as a source of cortical control signals in individuals with tetraplegia

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

Biomedical Engineering Society, BMES, september 2007 (conference)

[BibTex]

Simeral, J. D., Kim, S. P., Black, M. J., Donoghue, J. P., Hochberg, L. R. Ensemble spiking activity as a source of cortical control signals in individuals with tetraplegia Biomedical Engineering Society, BMES, september 2007 (conference)

[BibTex]

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Detailed human shape and pose from images

Balan, A., Sigal, L., Black, M. J., Davis, J., Haussecker, H.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, pages: 1-8, Minneapolis, June 2007 (inproceedings)

pdf YouTube [BibTex]

Balan, A., Sigal, L., Black, M. J., Davis, J., Haussecker, H. Detailed human shape and pose from images In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, pages: 1-8, Minneapolis, June 2007 (inproceedings)

pdf YouTube [BibTex]

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Decoding grasp aperture from motor-cortical population activity

Artemiadis, P., Shakhnarovich, G., Vargas-Irwin, C., Donoghue, J. P., Black, M. J.

In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 518-521, May 2007 (inproceedings)

pdf [BibTex]

Artemiadis, P., Shakhnarovich, G., Vargas-Irwin, C., Donoghue, J. P., Black, M. J. Decoding grasp aperture from motor-cortical population activity In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 518-521, May 2007 (inproceedings)

pdf [BibTex]

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Multi-state decoding of point-and-click control signals from motor cortical activity in a human with tetraplegia

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

In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 486-489, May 2007 (inproceedings)

Abstract
Basic neural-prosthetic control of a computer cursor has been recently demonstrated by Hochberg et al. [1] using the BrainGate system (Cyberkinetics Neurotechnology Systems, Inc.). While these results demonstrate the feasibility of intracortically-driven prostheses for humans with paralysis, a practical cursor-based computer interface requires more precise cursor control and the ability to “click” on areas of interest. Here we present a practical point and click device that decodes both continuous states (e.g. cursor kinematics) and discrete states (e.g. click state) from single neural population in human motor cortex. We describe a probabilistic multi-state decoder and the necessary training paradigms that enable point and click cursor control by a human with tetraplegia using an implanted microelectrode array. We present results from multiple recording sessions and quantify the point and click performance.

pdf [BibTex]

Kim, S., Simeral, J., Hochberg, L., Donoghue, J. P., Friehs, G., Black, M. J. Multi-state decoding of point-and-click control signals from motor cortical activity in a human with tetraplegia In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 486-489, May 2007 (inproceedings)

pdf [BibTex]

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Deterministic Annealing for Multiple-Instance Learning

Gehler, P., Chapelle, O.

In Artificial Intelligence and Statistics (AIStats), 2007 (inproceedings)

pdf [BibTex]

Gehler, P., Chapelle, O. Deterministic Annealing for Multiple-Instance Learning In Artificial Intelligence and Statistics (AIStats), 2007 (inproceedings)

pdf [BibTex]

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Point-and-click cursor control by a person with tetraplegia using an intracortical neural interface system

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

Program No. 517.2. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Kim, S., Simeral, J. D., Hochberg, L. R., Friehs, G., Donoghue, J. P., Black, M. J. Point-and-click cursor control by a person with tetraplegia using an intracortical neural interface system Program No. 517.2. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

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Learning Appearances with Low-Rank SVM

Wolf, L., Jhuang, H., Hazan, T.

In Conference on Computer Vision and Pattern Recognition (CVPR), 2007 (inproceedings)

pdf [BibTex]

Wolf, L., Jhuang, H., Hazan, T. Learning Appearances with Low-Rank SVM In Conference on Computer Vision and Pattern Recognition (CVPR), 2007 (inproceedings)

pdf [BibTex]

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Neural correlates of grip aperture in primary motor cortex

Vargas-Irwin, C., Shakhnarovich, G., Artemiadis, P., Donoghue, J. P., Black, M. J.

Program No. 517.10. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Vargas-Irwin, C., Shakhnarovich, G., Artemiadis, P., Donoghue, J. P., Black, M. J. Neural correlates of grip aperture in primary motor cortex Program No. 517.10. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

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Directional tuning in motor cortex of a person with ALS

Simeral, J. D., Donoghue, J. P., Black, M. J., Friehs, G. M., Brown, R. H., Krivickas, L. S., Hochberg, L. R.

Program No. 517.4. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Simeral, J. D., Donoghue, J. P., Black, M. J., Friehs, G. M., Brown, R. H., Krivickas, L. S., Hochberg, L. R. Directional tuning in motor cortex of a person with ALS Program No. 517.4. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

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Steerable random fields

(Best Paper Award, INI-Graphics Net, 2008)

Roth, S., Black, M. J.

In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, 2007 (inproceedings)

pdf [BibTex]

Roth, S., Black, M. J. Steerable random fields In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, 2007 (inproceedings)

pdf [BibTex]

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Toward standardized assessment of pointing devices for brain-computer interfaces

Donoghue, J., Simeral, J., Kim, S., G.M. Friehs, L. H., Black, M.

Program No. 517.16. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Donoghue, J., Simeral, J., Kim, S., G.M. Friehs, L. H., Black, M. Toward standardized assessment of pointing devices for brain-computer interfaces Program No. 517.16. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

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A Biologically Inspired System for Action Recognition

Jhuang, H., Serre, T., Wolf, L., Poggio, T.

In International Conference on Computer Vision (ICCV), 2007 (inproceedings)

code pdf [BibTex]

Jhuang, H., Serre, T., Wolf, L., Poggio, T. A Biologically Inspired System for Action Recognition In International Conference on Computer Vision (ICCV), 2007 (inproceedings)

code pdf [BibTex]

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AREADNE Research in Encoding And Decoding of Neural Ensembles

Shakhnarovich, G., Hochberg, L. R., Donoghue, J. P., Stein, J., Brown, R. H., Krivickas, L. S., Friehs, G. M., Black, M. J.

Program No. 517.8. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Shakhnarovich, G., Hochberg, L. R., Donoghue, J. P., Stein, J., Brown, R. H., Krivickas, L. S., Friehs, G. M., Black, M. J. AREADNE Research in Encoding And Decoding of Neural Ensembles Program No. 517.8. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

2005

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A quantitative evaluation of video-based 3D person tracking

Balan, A. O., Sigal, L., Black, M. J.

In The Second Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS, pages: 349-356, October 2005 (inproceedings)

pdf [BibTex]

2005

Balan, A. O., Sigal, L., Black, M. J. A quantitative evaluation of video-based 3D person tracking In The Second Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS, pages: 349-356, October 2005 (inproceedings)

pdf [BibTex]

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Inferring attentional state and kinematics from motor cortical firing rates

Wood, F., Prabhat, , Donoghue, J. P., Black, M. J.

In Proc. IEEE Engineering in Medicine and Biology Society, pages: 1544-1547, September 2005 (inproceedings)

pdf [BibTex]

Wood, F., Prabhat, , Donoghue, J. P., Black, M. J. Inferring attentional state and kinematics from motor cortical firing rates In Proc. IEEE Engineering in Medicine and Biology Society, pages: 1544-1547, September 2005 (inproceedings)

pdf [BibTex]

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Motor cortical decoding using an autoregressive moving average model

Fisher, J., Black, M. J.

In Proc. IEEE Engineering in Medicine and Biology Society, pages: 1469-1472, September 2005 (inproceedings)

pdf [BibTex]

Fisher, J., Black, M. J. Motor cortical decoding using an autoregressive moving average model In Proc. IEEE Engineering in Medicine and Biology Society, pages: 1469-1472, September 2005 (inproceedings)

pdf [BibTex]

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Fields of Experts: A framework for learning image priors

Roth, S., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition, 2, pages: 860-867, June 2005 (inproceedings)

pdf [BibTex]

Roth, S., Black, M. J. Fields of Experts: A framework for learning image priors In IEEE Conf. on Computer Vision and Pattern Recognition, 2, pages: 860-867, June 2005 (inproceedings)

pdf [BibTex]

Thumb xl iccv05roth
On the spatial statistics of optical flow

(Marr Prize, Honorable Mention)

Roth, S., Black, M. J.

In International Conf. on Computer Vision, International Conf. on Computer Vision, pages: 42-49, 2005 (inproceedings)

pdf [BibTex]

Roth, S., Black, M. J. On the spatial statistics of optical flow In International Conf. on Computer Vision, International Conf. on Computer Vision, pages: 42-49, 2005 (inproceedings)

pdf [BibTex]

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Modeling neural population spiking activity with Gibbs distributions

Wood, F., Roth, S., Black, M. J.

In Advances in Neural Information Processing Systems 18, pages: 1537-1544, 2005 (inproceedings)

pdf [BibTex]

Wood, F., Roth, S., Black, M. J. Modeling neural population spiking activity with Gibbs distributions In Advances in Neural Information Processing Systems 18, pages: 1537-1544, 2005 (inproceedings)

pdf [BibTex]

no image
Energy-based models of motor cortical population activity

Wood, F., Black, M.

Program No. 689.20. 2005 Abstract Viewer/Itinerary Planner, Society for Neuroscience, Washington, DC, 2005 (conference)

abstract [BibTex]

Wood, F., Black, M. Energy-based models of motor cortical population activity Program No. 689.20. 2005 Abstract Viewer/Itinerary Planner, Society for Neuroscience, Washington, DC, 2005 (conference)

abstract [BibTex]

1993

Thumb xl bildschirmfoto 2013 01 14 um 11.48.36
Mixture models for optical flow computation

Jepson, A., Black, M.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-93, pages: 760-761, New York, NY, June 1993 (inproceedings)

pdf abstract tech report [BibTex]

1993

Jepson, A., Black, M. Mixture models for optical flow computation In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-93, pages: 760-761, New York, NY, June 1993 (inproceedings)

pdf abstract tech report [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 11.52.45
A framework for the robust estimation of optical flow

(Helmholtz Prize)

Black, M. J., Anandan, P.

In Fourth International Conf. on Computer Vision, ICCV-93, pages: 231-236, Berlin, Germany, May 1993 (inproceedings)

Abstract
Most approaches for estimating optical flow assume that, within a finite image region, only a single motion is present. This single motion assumption is violated in common situations involving transparency, depth discontinuities, independently moving objects, shadows, and specular reflections. To robustly estimate optical flow, the single motion assumption must be relaxed. This work describes a framework based on robust estimation that addresses violations of the brightness constancy and spatial smoothness assumptions caused by multiple motions. We show how the robust estimation framework can be applied to standard formulations of the optical flow problem thus reducing their sensitivity to violations of their underlying assumptions. The approach has been applied to three standard techniques for recovering optical flow: area-based regression, correlation, and regularization with motion discontinuities. This work focuses on the recovery of multiple parametric motion models within a region as well as the recovery of piecewise-smooth flow fields and provides examples with natural and synthetic image sequences.

pdf video abstract code [BibTex]

Black, M. J., Anandan, P. A framework for the robust estimation of optical flow In Fourth International Conf. on Computer Vision, ICCV-93, pages: 231-236, Berlin, Germany, May 1993 (inproceedings)

pdf video abstract code [BibTex]

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Action, representation, and purpose: Re-evaluating the foundations of computational vision

Black, M. J., Aloimonos, Y., Brown, C. M., Horswill, I., Malik, J., G. Sandini, , Tarr, M. J.

In International Joint Conference on Artificial Intelligence, IJCAI-93, pages: 1661-1666, Chambery, France, 1993 (inproceedings)

pdf [BibTex]

Black, M. J., Aloimonos, Y., Brown, C. M., Horswill, I., Malik, J., G. Sandini, , Tarr, M. J. Action, representation, and purpose: Re-evaluating the foundations of computational vision In International Joint Conference on Artificial Intelligence, IJCAI-93, pages: 1661-1666, Chambery, France, 1993 (inproceedings)

pdf [BibTex]