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» Recovering Human Body Configurations: Combining Segmentation...
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CVPR
2004
IEEE
14 years 7 months ago
Recovering Human Body Configurations: Combining Segmentation and Recognition
The goal of this work is to take an image such as the one in Figure 1(a), detect a human figure, and localize his joints and limbs (b) along with their associated pixel masks (c)....
Greg Mori, Xiaofeng Ren, Alexei A. Efros, Jitendra...
ICCV
2003
IEEE
14 years 7 months ago
Fusion of Static and Dynamic Body Biometrics for Gait Recognition
Human identification at a distance has recently gained growing interest from computer vision researchers. This paper aims to propose a visual recognition algorithm based upon fusi...
Liang Wang, Huazhong Ning, Tieniu Tan, Weiming Hu
ICPR
2008
IEEE
13 years 11 months ago
Full body tracking-based human action recognition
In this paper, we present a novel method for human action recognition with the combined global movement feature and local configuration feature. The human action is represented as...
Junxia Gu, Xiaoqing Ding, Shengjin Wang, Youshou W...
CVPR
2003
IEEE
14 years 7 months ago
Finding and Tracking People from the Bottom Up
We describe a tracker that can track moving people in long sequences without manual initialization. Moving people are modeled with the assumption that, while configuration can var...
Deva Ramanan, David A. Forsyth
CVPR
2010
IEEE
1182views Computer Vision» more  CVPR 2010»
14 years 1 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...