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
Articulated Body Motion Capture by Stochastic Search
International Journal of Computer Vision
Monocular 3-D Tracking of the Golf Swing
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Kernel Particle Filter for Real-Time 3D Body Tracking in Monocular Color Images
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Feature Extraction & Image Processing, Second Edition
Feature Extraction & Image Processing, Second Edition
Recognizing and interpreting gestures on a mobile robot
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel appearance-adaptive models for real-time object tracking using particle swarm optimization
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
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This paper presents a model-based approach to monocular tracking of human body using a non-calibrated camera. The tracking in monocular images is realized using a particle filter and an articulated 3D model with a cylinder-based representation of the body. In modeling the visual appearance of the person we employ appearance-adaptive models. The predominant orientation of the gradient combined with ridge cues provides strong orientation responses in the observation model of the particle filter. The phase that is measured using the Gabor filter contributes towards strong localization of the body limbs. The potential of our approach is demonstrated by tracking of the human body on real videos.