Probabilistic Methods for Finding People
International Journal of Computer Vision
Probabilistic Tracking with Exemplars in a Metric Space
International Journal of Computer Vision - Marr Prize Special Issue
Estimating Human Body Configurations Using Shape Context Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
A Variational Framework for Joint Segmentation and Registration
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Twist Based Acquisition and Tracking of Animal and Human Kinematics
International Journal of Computer Vision
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Strike a Pose: Tracking People by Finding Stylized Poses
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Recovering Human Body Configurations Using Pairwise Constraints between Parts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Guiding Model Search Using Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Temporal motion models for monocular and multiview 3D human body tracking
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraint Integration for Efficient Multiview Pose Estimation with Self-Occlusions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous Segmentation and Pose Estimation of Humans Using Dynamic Graph Cuts
International Journal of Computer Vision
Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
A linear programming based method for joint object region matching and labeling
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
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We propose a novel method to detect human poses in videos by concurrently optimizing body part matching and object segmentation. With a single exemplar image, the proposed method detects the poses of a specific human subject in long video sequences. Matching and segmentation support each other and therefore the simultaneous optimization enables more reliable results. However, efficient concurrent optimization is a great challenge due to its huge search space. We propose an efficient linear method that solves the problem. In this method, the optimal body part matching conforms to local appearances and a human body plan, and the body part configuration is consistent with the object foreground estimated by simultaneous superpixel labeling. Our experiments on a variety of videos show that the proposed method is efficient and more reliable than previous locally constrained approaches.