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» Probabilistic Parameter-Free Motion Detection
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CVPR
2005
IEEE
14 years 9 months ago
Hybrid Models for Human Motion Recognition
Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
Claudio Fanti, Lihi Zelnik-Manor, Pietro Perona
CVPR
2007
IEEE
14 years 9 months ago
Learning Motion Categories using both Semantic and Structural Information
Current approaches to motion category recognition typically focus on either full spatiotemporal volume analysis (holistic approach) or analysis of the content of spatiotemporal in...
Shu-Fai Wong, Tae-Kyun Kim, Roberto Cipolla
CRV
2009
IEEE
217views Robotics» more  CRV 2009»
14 years 2 months ago
Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images
Understanding the human gait is an important objective towards improving elderly mobility. In turn, gait analyses largely depend on kinematic and dynamic measurements. While the m...
Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal P...
CVPR
2008
IEEE
14 years 9 months ago
Real-time pose estimation of articulated objects using low-level motion
We present a method that is capable of tracking and estimating pose of articulated objects in real-time. This is achieved by using a bottom-up approach to detect instances of the ...
Ben Daubney, David P. Gibson, Neill W. Campbell
MMM
2007
Springer
123views Multimedia» more  MMM 2007»
14 years 1 months ago
Tamper Proofing 3D Motion Data Streams
This paper presents a fragile watermarking technique to tamper proof (Mocap) motion capture data. The technique visualizes 3D Mocap data as a series of cluster of points. Watermark...
Parag Agarwal, Balakrishnan Prabhakaran