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CVPR
2006
IEEE
14 years 9 months ago
Spatial Divide and Conquer with Motion Cues for Tracking through Clutter
Tracking can be considered a two-class classification problem between the foreground object and its surrounding background. Feature selection to better discriminate object from ba...
Zhaozheng Yin, Robert T. Collins
BILDMED
2006
170views Algorithms» more  BILDMED 2006»
13 years 8 months ago
Fully-Automated Analysis of Muscle Fiber Images with Combined Region and Edge-Based Active Contours
This paper presents a new approach to automated muscle fiber analysis based on segmenting myofibers with combined region and edge based active contours. It provides reliable and fu...
Thomas Brox, Yoo-Jin Kim, Joachim Weickert, Wolfga...
CVPR
2009
IEEE
1524views Computer Vision» more  CVPR 2009»
15 years 2 months ago
3D Pose Estimation and Segmentation using Specular Cues
We present a system for fast model-based segmentation and 3D pose estimation of specular objects using appearance based specular features. We use observed (a) specular reflection...
Ju Yong Chang, Ramesh Raskar, Amit K. Agrawal
CVPR
2007
IEEE
14 years 9 months ago
Tracking as Repeated Figure/Ground Segmentation
Tracking over a long period of time is challenging as the appearance, shape and scale of the object in question may vary. We propose a paradigm of tracking by repeatedly segmentin...
Xiaofeng Ren, Jitendra Malik
ECCV
1998
Springer
14 years 9 months ago
Concerning Bayesian Motion Segmentation, Model, Averaging, Matching and the Trifocal Tensor
Abstract. Motion segmentation involves identifying regions of the image that correspond to independently moving objects. The number of independently moving objects, and type of mot...
Philip H. S. Torr, Andrew Zisserman