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2010


Thumb xl screen shot 2012 12 01 at 2.37.12 pm
Visibility Maps for Improving Seam Carving

Mansfield, A., Gehler, P., Van Gool, L., Rother, C.

In Media Retargeting Workshop, European Conference on Computer Vision (ECCV), september 2010 (inproceedings)

webpage pdf slides supplementary code [BibTex]

2010

webpage pdf slides supplementary code [BibTex]


Thumb xl eigenclothingimagesmall2
A 2D human body model dressed in eigen clothing

Guan, P., Freifeld, O., Black, M. J.

In European Conf. on Computer Vision, (ECCV), pages: 285-298, Springer-Verlag, September 2010 (inproceedings)

Abstract
Detection, tracking, segmentation and pose estimation of people in monocular images are widely studied. Two-dimensional models of the human body are extensively used, however, they are typically fairly crude, representing the body either as a rough outline or in terms of articulated geometric primitives. We describe a new 2D model of the human body contour that combines an underlying naked body with a low-dimensional clothing model. The naked body is represented as a Contour Person that can take on a wide variety of poses and body shapes. Clothing is represented as a deformation from the underlying body contour. This deformation is learned from training examples using principal component analysis to produce eigen clothing. We find that the statistics of clothing deformations are skewed and we model the a priori probability of these deformations using a Beta distribution. The resulting generative model captures realistic human forms in monocular images and is used to infer 2D body shape and pose under clothing. We also use the coefficients of the eigen clothing to recognize different categories of clothing on dressed people. The method is evaluated quantitatively on synthetic and real images and achieves better accuracy than previous methods for estimating body shape under clothing.

pdf data poster Project Page [BibTex]

pdf data poster Project Page [BibTex]


Thumb xl teaser eccvw
Analyzing and Evaluating Markerless Motion Tracking Using Inertial Sensors

Baak, A., Helten, T., Müller, M., Pons-Moll, G., Rosenhahn, B., Seidel, H.

In European Conference on Computer Vision (ECCV Workshops), September 2010 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl testing results 1
Trainable, Vision-Based Automated Home Cage Behavioral Phenotyping

Jhuang, H., Garrote, E., Edelman, N., Poggio, T., Steele, A., Serre, T.

In Measuring Behavior, August 2010 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl graspimagesmall
Decoding complete reach and grasp actions from local primary motor cortex populations

(Featured in Nature’s Research Highlights (Nature, Vol 466, 29 July 2010))

Vargas-Irwin, C. E., Shakhnarovich, G., Yadollahpour, P., Mislow, J., Black, M. J., Donoghue, J. P.

J. of Neuroscience, 39(29):9659-9669, July 2010 (article)

pdf pdf from publisher Movie 1 Movie 2 Project Page [BibTex]

pdf pdf from publisher Movie 1 Movie 2 Project Page [BibTex]


Thumb xl teaser cvpr2010
Multisensor-Fusion for 3D Full-Body Human Motion Capture

Pons-Moll, G., Baak, A., Helten, T., Müller, M., Seidel, H., Rosenhahn, B.

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2010 (inproceedings)

project page pdf [BibTex]

project page pdf [BibTex]


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Coded exposure imaging for projective motion deblurring

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

In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages: 2408-2415, June 2010 (inproceedings)

Abstract
We propose a method for deblurring of spatially variant object motion. A principal challenge of this problem is how to estimate the point spread function (PSF) of the spatially variant blur. Based on the projective motion blur model of, we present a blur estimation technique that jointly utilizes a coded exposure camera and simple user interactions to recover the PSF. With this spatially variant PSF, objects that exhibit projective motion can be effectively de-blurred. We validate this method with several challenging image examples.

Publisher site [BibTex]

Publisher site [BibTex]


Thumb xl cvpr10
Tracking people interacting with objects

Kjellstrom, H., Kragic, D., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, pages: 747-754, June 2010 (inproceedings)

pdf Video [BibTex]

pdf Video [BibTex]


Thumb xl contourpersonimagesmall
Contour people: A parameterized model of 2D articulated human shape

Freifeld, O., Weiss, A., Zuffi, S., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition, (CVPR), pages: 639-646, IEEE, June 2010 (inproceedings)

pdf slides video of CVPR talk Project Page [BibTex]

pdf slides video of CVPR talk Project Page [BibTex]


Thumb xl secretsimagesmall2
Secrets of optical flow estimation and their principles

Sun, D., Roth, S., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 2432-2439, IEEE, June 2010 (inproceedings)

pdf Matlab code code copryright notice [BibTex]

pdf Matlab code code copryright notice [BibTex]


Thumb xl ijcvcoverhd
Guest editorial: State of the art in image- and video-based human pose and motion estimation

Sigal, L., Black, M. J.

International Journal of Computer Vision, 87(1):1-3, March 2010 (article)

pdf from publisher [BibTex]

pdf from publisher [BibTex]


Thumb xl humanevaimagesmall2
HumanEva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion

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

International Journal of Computer Vision, 87(1):4-27, Springer Netherlands, March 2010 (article)

Abstract
While research on articulated human motion and pose estimation has progressed rapidly in the last few years, there has been no systematic quantitative evaluation of competing methods to establish the current state of the art. We present data obtained using a hardware system that is able to capture synchronized video and ground-truth 3D motion. The resulting HumanEva datasets contain multiple subjects performing a set of predefined actions with a number of repetitions. On the order of 40,000 frames of synchronized motion capture and multi-view video (resulting in over one quarter million image frames in total) were collected at 60 Hz with an additional 37,000 time instants of pure motion capture data. A standard set of error measures is defined for evaluating both 2D and 3D pose estimation and tracking algorithms. We also describe a baseline algorithm for 3D articulated tracking that uses a relatively standard Bayesian framework with optimization in the form of Sequential Importance Resampling and Annealed Particle Filtering. In the context of this baseline algorithm we explore a variety of likelihood functions, prior models of human motion and the effects of algorithm parameters. Our experiments suggest that image observation models and motion priors play important roles in performance, and that in a multi-view laboratory environment, where initialization is available, Bayesian filtering tends to perform well. The datasets and the software are made available to the research community. This infrastructure will support the development of new articulated motion and pose estimation algorithms, will provide a baseline for the evaluation and comparison of new methods, and will help establish the current state of the art in human pose estimation and tracking.

pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]


no image
Modellbasierte Echtzeit-Bewegungsschätzung in der Fluoreszenzendoskopie

Stehle, T., Wulff, J., Behrens, A., Gross, S., Aach, T.

In Bildverarbeitung für die Medizin, 574, pages: 435-439, CEUR Workshop Proceedings, 2010 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl acva2010
Robust one-shot 3D scanning using loopy belief propagation

Ulusoy, A., Calakli, F., Taubin, G.

In Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on, pages: 15-22, IEEE, 2010 (inproceedings)

Abstract
A structured-light technique can greatly simplify the problem of shape recovery from images. There are currently two main research challenges in design of such techniques. One is handling complicated scenes involving texture, occlusions, shadows, sharp discontinuities, and in some cases even dynamic change; and the other is speeding up the acquisition process by requiring small number of images and computationally less demanding algorithms. This paper presents a “one-shot” variant of such techniques to tackle the aforementioned challenges. It works by projecting a static grid pattern onto the scene and identifying the correspondence between grid stripes and the camera image. The correspondence problem is formulated using a novel graphical model and solved efficiently using loopy belief propagation. Unlike prior approaches, the proposed approach uses non-deterministic geometric constraints, thereby can handle spurious connections of stripe images. The effectiveness of the proposed approach is verified on a variety of complicated real scenes.

pdf link (url) DOI [BibTex]

pdf link (url) DOI [BibTex]


Thumb xl screen shot 2012 12 01 at 2.43.22 pm
Scene Carving: Scene Consistent Image Retargeting

Mansfield, A., Gehler, P., Van Gool, L., Rother, C.

In European Conference on Computer Vision (ECCV), 2010 (inproceedings)

webpage+code pdf supplementary poster [BibTex]

webpage+code pdf supplementary poster [BibTex]


Thumb xl new thumb incos
Epione: An Innovative Pain Management System Using Facial Expression Analysis, Biofeedback and Augmented Reality-Based Distraction

Georgoulis, S., Eleftheriadis, S., Tzionas, D., Vrenas, K., Petrantonakis, P., Hadjileontiadis, L. J.

In Proceedings of the 2010 International Conference on Intelligent Networking and Collaborative Systems, pages: 259-266, INCOS ’10, IEEE Computer Society, Washington, DC, USA, 2010 (inproceedings)

Abstract
An innovative pain management system, namely Epione, is presented here. Epione deals with three main types of pain, i.e., acute pain, chronic pain, and phantom limb pain. In particular, by using facial expression analysis, Epione forms a dynamic pain meter, which then triggers biofeedback and augmented reality-based destruction scenarios, in an effort to maximize patient's pain relief. This unique combination sets Epione not only a novel pain management approach, but also a means that provides an understanding and integration of the needs of the whole community involved i.e., patients and physicians, in a joint attempt to facilitate easing of their suffering, provide efficient monitoring and contribute to a better quality of life.

Paper Project Page DOI [BibTex]

Paper Project Page DOI [BibTex]


Thumb xl new thumb dsai
Phantom Limb Pain Management Using Facial Expression Analysis, Biofeedback and Augmented Reality Interfacing

Tzionas, D., Vrenas, K., Eleftheriadis, S., Georgoulis, S., Petrantonakis, P. C., Hadjileontiadis, L. J.

In Proceedings of the 3rd International Conferenceon Software Development for EnhancingAccessibility and Fighting Info-Exclusion, pages: 23-30, DSAI ’10, UTAD - Universidade de Trás-os-Montes e Alto Douro, 2010 (inproceedings)

Abstract
Post-amputation sensation often translates to the feeling of severe pain in the missing limb, referred to as phantom limb pain (PLP). A clear and rational treatment regimen is difficult to establish, as long as the underlying pathophysiology is not fully known. In this work, an innovative PLP management system is presented, as a module of an holistic computer-mediated pain management environment, namely Epione. The proposed Epione-PLP scheme is structured upon advanced facial expression analysis, used to form a dynamic pain meter, which, in turn, is used to trigger biofeedback and augmented reality-based PLP distraction scenarios. The latter incorporate a model of the missing limb for its visualization, in an effort to provide to the amputee the feeling of its existence and control, and, thus, maximize his/her PLP relief. The novel Epione-PLP management approach integrates edge-technology within the context of personalized health and it could be used to facilitate easing of PLP patients' suffering, provide efficient progress monitoring and contribute to the increase in their quality of life.

Paper Project Page link (url) [BibTex]

Paper Project Page link (url) [BibTex]


Thumb xl ncomm fig2
Automated Home-Cage Behavioral Phenotyping of Mice

Jhuang, H., Garrote, E., Mutch, J., Poggio, T., Steele, A., Serre, T.

Nature Communications, Nature Communications, 2010 (article)

software, demo pdf [BibTex]

software, demo pdf [BibTex]


no image
An automated action initiation system reveals behavioral deficits in MyosinVa deficient mice

Pandian, S., Edelman, N., Jhuang, H., Serre, T., Poggio, T., Constantine-Paton, M.

Society for Neuroscience, 2010 (conference)

pdf [BibTex]

pdf [BibTex]


Thumb xl vista
Dense Marker-less Three Dimensional Motion Capture

Soren Hauberg, Bente Rona Jensen, Morten Engell-Norregaard, Kenny Erleben, Kim S. Pedersen

In Virtual Vistas; Eleventh International Symposium on the 3D Analysis of Human Movement, 2010 (inproceedings)

Conference site [BibTex]

Conference site [BibTex]


Thumb xl accv2010
Stick It! Articulated Tracking using Spatial Rigid Object Priors

Soren Hauberg, Kim S. Pedersen

In Computer Vision – ACCV 2010, 6494, pages: 758-769, Lecture Notes in Computer Science, (Editors: Kimmel, Ron and Klette, Reinhard and Sugimoto, Akihiro), Springer Berlin Heidelberg, 2010 (inproceedings)

Publishers site Paper site Code PDF [BibTex]

Publishers site Paper site Code PDF [BibTex]


Thumb xl eccv2010a
Gaussian-like Spatial Priors for Articulated Tracking

Soren Hauberg, Stefan Sommer, Kim S. Pedersen

In Computer Vision – ECCV 2010, 6311, pages: 425-437, Lecture Notes in Computer Science, (Editors: Daniilidis, Kostas and Maragos, Petros and Paragios, Nikos), Springer Berlin Heidelberg, 2010 (inproceedings)

Publishers site Paper site Code PDF [BibTex]

Publishers site Paper site Code PDF [BibTex]


no image
Reach to grasp actions in rhesus macaques: Dimensionality reduction of hand, wrist, and upper arm motor subspaces using principal component analysis

Vargas-Irwin, C., Franquemont, L., Shakhnarovich, G., Yadollahpour, P., Black, M., Donoghue, J.

2010 Abstract Viewer and Itinerary Planner, Society for Neuroscience, 2010, Online (conference)

[BibTex]

[BibTex]


Thumb xl nips2010layersimagesmall
Layered image motion with explicit occlusions, temporal consistency, and depth ordering

Sun, D., Sudderth, E., Black, M. J.

In Advances in Neural Information Processing Systems 23 (NIPS), pages: 2226-2234, MIT Press, 2010 (inproceedings)

Abstract
Layered models are a powerful way of describing natural scenes containing smooth surfaces that may overlap and occlude each other. For image motion estimation, such models have a long history but have not achieved the wide use or accuracy of non-layered methods. We present a new probabilistic model of optical flow in layers that addresses many of the shortcomings of previous approaches. In particular, we define a probabilistic graphical model that explicitly captures: 1) occlusions and disocclusions; 2) depth ordering of the layers; 3) temporal consistency of the layer segmentation. Additionally the optical flow in each layer is modeled by a combination of a parametric model and a smooth deviation based on an MRF with a robust spatial prior; the resulting model allows roughness in layers. Finally, a key contribution is the formulation of the layers using an image dependent hidden field prior based on recent models for static scene segmentation. The method achieves state-of-the-art results on the Middlebury benchmark and produces meaningful scene segmentations as well as detected occlusion regions.

main paper supplemental material paper and supplemental material in one pdf file Project Page [BibTex]


Thumb xl eccv2010b
Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations

Stefan Sommer, Francois Lauze, Soren Hauberg, Mads Nielsen

In Computer Vision – ECCV 2010, 6316, pages: 43-56, (Editors: Daniilidis, Kostas and Maragos, Petros and Paragios, Nikos), Springer Berlin Heidelberg, 2010 (inproceedings)

Publishers site PDF [BibTex]

Publishers site PDF [BibTex]


Thumb xl cvgpu2010
GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking

Rune Mollegaard Friborg, Soren Hauberg, Kenny Erleben

In The CVGPU workshop at European Conference on Computer Vision (ECCV) 2010, 2010 (inproceedings)

PDF [BibTex]

PDF [BibTex]


Thumb xl thumb screen shot 2012 10 06 at 12.00.36 pm
Visual Object-Action Recognition: Inferring Object Affordances from Human Demonstration

Kjellström, H., Romero, J., Kragic, D.

Computer Vision and Image Understanding, pages: 81-90, 2010 (article)

Pdf [BibTex]

Pdf [BibTex]


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Unsupervised learning of a low-dimensional non-linear representation of motor cortical neuronal ensemble activity using Spatio-Temporal Isomap

Kim, S., Tsoli, A., Jenkins, O., Simeral, J., Donoghue, J., Black, M.

2010 Abstract Viewer and Itinerary Planner, Society for Neuroscience, 2010, Online (conference)

[BibTex]

[BibTex]


Thumb xl segmentation miccai10
3D Knowledge-Based Segmentation Using Pose-Invariant Higher-Order Graphs

Wang, C., Teboul, O., Michel, F., Essafi, S., Paragios, N.

In International Conference, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2010 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl testing results 1
Vision-Based Automated Recognition of Mice Home-Cage Behaviors.

Jhuang, H., Garrote, E., Edelman, N., Poggio, T., Steele, A., Serre, T.

Workshop: Visual Observation and Analysis of Animal and Insect Behavior, in conjunction with International Conference on Pattern Recognition (ICPR) , 2010 (conference)

pdf [BibTex]

pdf [BibTex]


Thumb xl thumb screen shot 2012 10 06 at 11.52.35 am
Hands in action: real-time 3D reconstruction of hands in interaction with objects

Romero, J., Kjellström, H., Kragic, D.

In IEEE International Conference on Robotics and Automation (ICRA), pages: 458-463, 2010 (inproceedings)

Pdf Project Page [BibTex]

Pdf Project Page [BibTex]


no image
Orientation and direction selectivity in the population code of the visual thalamus

Stanley, G., Jin, J., Wang, Y., Desbordes, G., Black, M., Alonso, J.

COSYNE, 2010 (conference)

[BibTex]

[BibTex]


Thumb xl brightchannel
Estimating Shadows with the Bright Channel Cue

Panagopoulos, A., Wang, C., Samaras, D., Paragios, N.

In Color and Reflectance in Imaging and Computer Vision Workshop (CRICV) (in conjunction with ECCV 2010), 2010 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl shapematching cvpr10
Dense non-rigid surface registration using high-order graph matching

Zeng, Y., Wang, C., Wang, Y., Gu, X., Samaras, D., Paragios, N.

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl screen shot 2012 02 23 at 5.52.02 pm
Computational Mechanisms for the motion processing in visual area MT

Jhuang, H., Serre, T., Poggio, T.

Society for Neuroscience, 2010 (conference)

pdf [BibTex]

pdf [BibTex]


Thumb xl thumb screen shot 2012 10 06 at 11.56.17 am
Spatio-Temporal Modeling of Grasping Actions

Romero, J., Feix, T., Kjellström, H., Kragic, D.

In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pages: 2103-2108, 2010 (inproceedings)

Pdf Project Page [BibTex]

Pdf Project Page [BibTex]

2000


Thumb xl ijcv2000teaser
Probabilistic detection and tracking of motion boundaries

Black, M. J., Fleet, D. J.

Int. J. of Computer Vision, 38(3):231-245, July 2000 (article)

Abstract
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are represented using a non-linear generative model that explicitly encodes the orientation of the boundary, the velocities on either side, the motion of the occluding edge over time, and the appearance/disappearance of pixels at the boundary. We represent the posterior probability distribution over the model parameters given the image data using discrete samples. This distribution is propagated over time using a particle filtering algorithm. To efficiently represent such a high-dimensional space we initialize samples using the responses of a low-level motion discontinuity detector. The formulation and computational model provide a general probabilistic framework for motion estimation with multiple, non-linear, models.

pdf pdf from publisher Video [BibTex]

2000

pdf pdf from publisher Video [BibTex]


Thumb xl bildschirmfoto 2012 12 11 um 12.12.25
Stochastic tracking of 3D human figures using 2D image motion

(Winner of the 2010 Koenderink Prize for Fundamental Contributions in Computer Vision)

Sidenbladh, H., Black, M. J., Fleet, D.

In European Conference on Computer Vision, ECCV, pages: 702-718, LNCS 1843, Springer Verlag, Dublin, Ireland, June 2000 (inproceedings)

Abstract
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appearance, a robust likelihood function based on image gray level differences, and a prior probability distribution over pose and joint angles that models how humans move. The posterior probability distribution over model parameters is represented using a discrete set of samples and is propagated over time using particle filtering. The approach extends previous work on parameterized optical flow estimation to exploit a complex 3D articulated motion model. It also extends previous work on human motion tracking by including a perspective camera model, by modeling limb self occlusion, and by recovering 3D motion from a monocular sequence. The explicit posterior probability distribution represents ambiguities due to image matching, model singularities, and perspective projection. The method relies only on a frame-to-frame assumption of brightness constancy and hence is able to track people under changing viewpoints, in grayscale image sequences, and with complex unknown backgrounds.

pdf code [BibTex]

pdf code [BibTex]


no image
Functional analysis of human motion data

Ormoneit, D., Hastie, T., Black, M. J.

In In Proc. 5th World Congress of the Bernoulli Society for Probability and Mathematical Statistics and 63rd Annual Meeting of the Institute of Mathematical Statistics, Guanajuato, Mexico, May 2000 (inproceedings)

[BibTex]

[BibTex]


no image
Stochastic modeling and tracking of human motion

Ormoneit, D., Sidenbladh, H., Black, M. J., Hastie, T.

Learning 2000, Snowbird, UT, April 2000 (conference)

abstract [BibTex]

abstract [BibTex]


Thumb xl bildschirmfoto 2012 12 12 um 11.40.47
A framework for modeling the appearance of 3D articulated figures

Sidenbladh, H., De la Torre, F., Black, M. J.

In Int. Conf. on Automatic Face and Gesture Recognition, pages: 368-375, Grenoble, France, March 2000 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 06 um 09.22.34
Design and use of linear models for image motion analysis

Fleet, D. J., Black, M. J., Yacoob, Y., Jepson, A. D.

Int. J. of Computer Vision, 36(3):171-193, 2000 (article)

Abstract
Linear parameterized models of optical flow, particularly affine models, have become widespread in image motion analysis. The linear model coefficients are straightforward to estimate, and they provide reliable estimates of the optical flow of smooth surfaces. Here we explore the use of parameterized motion models that represent much more varied and complex motions. Our goals are threefold: to construct linear bases for complex motion phenomena; to estimate the coefficients of these linear models; and to recognize or classify image motions from the estimated coefficients. We consider two broad classes of motions: i) generic “motion features” such as motion discontinuities and moving bars; and ii) non-rigid, object-specific, motions such as the motion of human mouths. For motion features we construct a basis of steerable flow fields that approximate the motion features. For object-specific motions we construct basis flow fields from example motions using principal component analysis. In both cases, the model coefficients can be estimated directly from spatiotemporal image derivatives with a robust, multi-resolution scheme. Finally, we show how these model coefficients can be use to detect and recognize specific motions such as occlusion boundaries and facial expressions.

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 06 um 09.48.16
Robustly estimating changes in image appearance

Black, M. J., Fleet, D. J., Yacoob, Y.

Computer Vision and Image Understanding, 78(1):8-31, 2000 (article)

Abstract
We propose a generalized model of image “appearance change” in which brightness variation over time is represented as a probabilistic mixture of different causes. We define four generative models of appearance change due to (1) object or camera motion; (2) illumination phenomena; (3) specular reflections; and (4) “iconic changes” which are specific to the objects being viewed. These iconic changes include complex occlusion events and changes in the material properties of the objects. We develop a robust statistical framework for recovering these appearance changes in image sequences. This approach generalizes previous work on optical flow to provide a richer description of image events and more reliable estimates of image motion in the presence of shadows and specular reflections.

pdf pdf from publisher DOI [BibTex]

pdf pdf from publisher DOI [BibTex]

1996


Thumb xl bildschirmfoto 2013 01 14 um 10.40.24
Cardboard people: A parameterized model of articulated motion

Ju, S. X., Black, M. J., Yacoob, Y.

In 2nd Int. Conf. on Automatic Face- and Gesture-Recognition, pages: 38-44, Killington, Vermont, October 1996 (inproceedings)

Abstract
We extend the work of Black and Yacoob on the tracking and recognition of human facial expressions using parameterized models of optical flow to deal with the articulated motion of human limbs. We define a "cardboard person model" in which a person's limbs are represented by a set of connected planar patches. The parameterized image motion of these patches is constrained to enforce articulated motion and is solved for directly using a robust estimation technique. The recovered motion parameters provide a rich and concise description of the activity that can be used for recognition. We propose a method for performing view-based recognition of human activities from the optical flow parameters that extends previous methods to cope with the cyclical nature of human motion. We illustrate the method with examples of tracking human legs over long image sequences.

pdf [BibTex]

1996

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 07 um 11.52.07
Estimating optical flow in segmented images using variable-order parametric models with local deformations

Black, M. J., Jepson, A.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(10):972-986, October 1996 (article)

Abstract
This paper presents a new model for estimating optical flow based on the motion of planar regions plus local deformations. The approach exploits brightness information to organize and constrain the interpretation of the motion by using segmented regions of piecewise smooth brightness to hypothesize planar regions in the scene. Parametric flow models are estimated in these regions in a two step process which first computes a coarse fit and estimates the appropriate parameterization of the motion of the region (two, six, or eight parameters). The initial fit is refined using a generalization of the standard area-based regression approaches. Since the assumption of planarity is likely to be violated, we allow local deformations from the planar assumption in the same spirit as physically-based approaches which model shape using coarse parametric models plus local deformations. This parametric+deformation model exploits the strong constraints of parametric approaches while retaining the adaptive nature of regularization approaches. Experimental results on a variety of images indicate that the parametric+deformation model produces accurate flow estimates while the incorporation of brightness segmentation provides precise localization of motion boundaries.

pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]


Thumb xl bildschirmfoto 2012 12 07 um 11.59.00
On the unification of line processes, outlier rejection, and robust statistics with applications in early vision

Black, M., Rangarajan, A.

International Journal of Computer Vision , 19(1):57-92, July 1996 (article)

Abstract
The modeling of spatial discontinuities for problems such as surface recovery, segmentation, image reconstruction, and optical flow has been intensely studied in computer vision. While “line-process” models of discontinuities have received a great deal of attention, there has been recent interest in the use of robust statistical techniques to account for discontinuities. This paper unifies the two approaches. To achieve this we generalize the notion of a “line process” to that of an analog “outlier process” and show how a problem formulated in terms of outlier processes can be viewed in terms of robust statistics. We also characterize a class of robust statistical problems for which an equivalent outlier-process formulation exists and give a straightforward method for converting a robust estimation problem into an outlier-process formulation. We show how prior assumptions about the spatial structure of outliers can be expressed as constraints on the recovered analog outlier processes and how traditional continuation methods can be extended to the explicit outlier-process formulation. These results indicate that the outlier-process approach provides a general framework which subsumes the traditional line-process approaches as well as a wide class of robust estimation problems. Examples in surface reconstruction, image segmentation, and optical flow are presented to illustrate the use of outlier processes and to show how the relationship between outlier processes and robust statistics can be exploited. An appendix provides a catalog of common robust error norms and their equivalent outlier-process formulations.

pdf pdf from publisher DOI [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 10.48.32
Skin and Bones: Multi-layer, locally affine, optical flow and regularization with transparency

(Nominated: Best paper)

Ju, S., Black, M. J., Jepson, A. D.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR’96, pages: 307-314, San Francisco, CA, June 1996 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 10.52.58
EigenTracking: Robust matching and tracking of articulated objects using a view-based representation

Black, M. J., Jepson, A.

In Proc. Fourth European Conf. on Computer Vision, ECCV’96, pages: 329-342, LNCS 1064, Springer Verlag, Cambridge, England, April 1996 (inproceedings)

pdf video [BibTex]

pdf video [BibTex]