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» Gaussian Process Dynamical Models for Human Motion
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NIPS
2004
15 years 1 months ago
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
We present a generative model and stochastic filtering algorithm for simultaneous tracking of 3D position and orientation, non-rigid motion, object texture, and background texture...
Tim K. Marks, John R. Hershey, J. Cooper Roddey, J...
CAPTECH
1998
Springer
15 years 4 months ago
3D Part Recognition Method for Human Motion Analysis
A method for matching sequences from two perspective views of a moving person silhouette is presented. Regular (approximate uniform thickness) parts are detected on an image and a ...
Carlos Yániz, Jairo Rocha, Francisco J. Per...
VLDB
2004
ACM
186views Database» more  VLDB 2004»
15 years 5 months ago
Indexing Large Human-Motion Databases
Data-driven animation has become the industry standard for computer games and many animated movies and special effects. In particular, motion capture data recorded from live actor...
Eamonn J. Keogh, Themis Palpanas, Victor B. Zordan...
ACCV
2009
Springer
15 years 6 months ago
Human Action Recognition Using HDP by Integrating Motion and Location Information
The method based on local features has an advantage that the important local motion feature is represented as bag-of-features, but lacks the location information. Additionally, in ...
Yasuo Ariki, Takuya Tonaru, Tetsuya Takiguchi
IJCV
2008
188views more  IJCV 2008»
14 years 12 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin