Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
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
Object Tracking with Bayesian Estimation of Dynamic Layer Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Performance animation from low-dimensional control signals
ACM SIGGRAPH 2005 Papers
Tracking of Multiple, Partially Occluded Humans based on Static Body Part Detection
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Vision Processing for Realtime 3-D Data Acquisition Based on Coded Structured Light
IEEE Transactions on Image Processing
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This paper presents the structure of our real time vision-based motion performance system. The system requires user to wear markers with a certain color. Several novel algorithms in the system are introduced including algorithms for feature detection and feature tracking under occlusion. Feature Detection takes advantages of four properties of markers to avoid the interference from non-markers regions. Besides, we propose a simple but effective method to track these features and handle occlusion by estimating velocity of missing features based on prior, smoothness and fitness term. These algorithms are to ensure the accuracy and low computation cost of reconstruction of 3D points of the markers. At run time, the system automatically scans, identifies, tracks and finally reconstructs the markers to 3D points. We test the ability of our system by having user perform walking, running and jumping.