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ICCV
2007
IEEE
15 years 4 months ago
Real-Time Automatic Kinematic Model Building for Optical Motion Capture Using a Markov Random Field
Abstract. We present a completely autonomous algorithm for the real-time creation of a moving subject’s kinematic model from optical motion capture data and with no a priori info...
Stjepan Rajko, Gang Qian
IROS
2007
IEEE
129views Robotics» more  IROS 2007»
15 years 4 months ago
Representability of human motions by factorial hidden Markov models
— This paper describes an improved methodology for human motion recognition and imitation based on Factorial Hidden Markov Models (FHMM). Unlike conventional Hidden Markov Models...
Dana Kulic, Wataru Takano, Yoshihiko Nakamura
ICCV
1999
IEEE
15 years 11 months ago
Capturing Articulated Human Hand Motion: A Divide-and-Conquer Approach
The use of human hand as a natural interface device serves as a motivating force for research in the modeling, analyzing and capturing of the motion of articulated hand. Model-bas...
Ying Wu, Thomas S. Huang
CVPR
2010
IEEE
1182views Computer Vision» more  CVPR 2010»
15 years 6 months ago
Real Time Motion Capture using a Single Time-Of-Flight Camera
Markerless tracking of human pose is a hard yet relevant problem. In this paper, we derive an efficient filtering algorithm for tracking human pose at 4-10 frames per second using...
Varun Ganapathi, Christian Plagemann, Sebastian Th...
ICIRA
2009
Springer
200views Robotics» more  ICIRA 2009»
15 years 4 months ago
Classifying 3D Human Motions by Mixing Fuzzy Gaussian Inference with Genetic Programming
This paper combines the novel concept of Fuzzy Gaussian Inference(FGI) with Genetic Programming (GP) in order to accurately classify real natural 3d human Motion Capture data. FGI ...
Mehdi Khoury, Honghai Liu