Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
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
3D articulated models and multiview tracking with physical forces
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Particle Filter with Analytical Inference for Human Body Tracking
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Stochastic Human Segmentation from a Static Camera
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
3D human body model acquisition from multiple views
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Tracking through Singularities and Discontinuities by Random Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Dynamic Human Pose Estimation using Markov Chain Monte Carlo Approach
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Human action recognition using star skeleton
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Representation and matching of articulated shapes
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Game System of Treadmill Based on Video Capture
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
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This paper presents two techniques for improving human bodytracking within the particle filtering scheme. Both techniquesexplore the use of auxiliary measurements. The first technique usesoptical flow cues to improve the sampling distribution. The secondtechnique involves the detection of individual body parts, namelythe hand, head and torso; and using these detection results toprovide additional inference on subsets of state parameters. Thismethod enables the automatic initialization of state vector andallows recovering from tracking failures. These two methods improvethe overall accuracy, efficiency and robustness of human bodytracking as illustrated by the experimental results.