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CVPR
2000
IEEE
15 years 8 months ago
Adaptive Bayesian Recognition in Tracking Rigid Objects
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Yuri Boykov, Daniel P. Huttenlocher
148
Voted
PAMI
2008
189views more  PAMI 2008»
15 years 3 months ago
Detecting Objects of Variable Shape Structure With Hidden State Shape Models
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...
153
Voted
TCSV
2002
229views more  TCSV 2002»
15 years 3 months ago
Automatic segmentation of moving objects in video sequences: a region labeling approach
Abstract--The emerging video coding standard MPEG-4 enables various content-based functionalities for multimedia applications. To support such functionalities, as well as to improv...
Yaakov Tsaig, Amir Averbuch
123
Voted
CVPR
2006
IEEE
16 years 5 months ago
Shape Guided Object Segmentation
We construct a Bayesian model that integrates topdown with bottom-up criteria, capitalizing on their relative merits to obtain figure-ground segmentation that is shape-specific an...
Eran Borenstein, Jitendra Malik
CVPR
2008
IEEE
16 years 5 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