A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Probabilistic Methods for Finding People
International Journal of Computer Vision
Machine Learning
The Image Foresting Transform: Theory, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pictorial Structures for Object Recognition
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CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Randomized Trees for Real-Time Keypoint Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Constrained optimization for human pose estimation from depth sequences
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
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3D human pose from silhouettes by relevance vector regression
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
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Real-time human pose recognition in parts from single depth images
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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Accurate 3D pose estimation from a single depth image
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Efficient regression of general-activity human poses from depth images
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Home 3D body scans from noisy image and range data
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Human body detection and pose estimation is useful for a wide variety of applications and environments. Therefore a human body detection and pose estimation system must be adaptable and customizable. This paper presents such a system that extracts skeletons from RGB-D sensor data. The system adapts on-line to difficult unstructured scenes taken from a moving camera (since it does not require background subtraction) and benefits from using both color and depth data. It is customizable by virtue of requiring less training data, having a clearly described training method, and a customizable human kinematic model. Results show successful application to data from a moving camera in cluttered indoor environments. This system is open-source, encouraging reuse, comparison, and future research.