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ICCV
2009
IEEE
2061views Computer Vision» more  ICCV 2009»
15 years 16 days ago
Background Subtraction for Freely Moving Cameras
Background subtraction algorithms define the background as parts of a scene that are at rest. Traditionally, these algorithms assume a stationary camera, and identify moving obj...
Yaser Sheikh, Omar Javed, Takeo Kanade
CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
14 years 9 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson
CVPR
2005
IEEE
14 years 9 months ago
Real-Time Non-Rigid Surface Detection
We present a real-time method for detecting deformable surfaces, with no need whatsoever for a priori pose knowledge. Our method starts from a set of wide baseline point matches b...
Julien Pilet, Vincent Lepetit, Pascal Fua
CVPR
2005
IEEE
14 years 9 months ago
Strike a Pose: Tracking People by Finding Stylized Poses
We develop an algorithm for finding and kinematically tracking multiple people in long sequences. Our basic assumption is that people tend to take on certain canonical poses, even...
Deva Ramanan, David A. Forsyth, Andrew Zisserman
CVPR
2008
IEEE
14 years 9 months ago
Drift-free tracking of rigid and articulated objects
Model-based 3D tracker estimate the position, rotation, and joint angles of a given model from video data of one or multiple cameras. They often rely on image features that are tr...
Juergen Gall, Bodo Rosenhahn, Hans-Peter Seidel