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CVPR
2007
IEEE
14 years 10 months ago
Beyond bottom-up: Incorporating task-dependent influences into a computational model of spatial attention
A critical function in both machine vision and biological vision systems is attentional selection of scene regions worthy of further analysis by higher-level processes such as obj...
Robert J. Peters, Laurent Itti
CVPR
1998
IEEE
14 years 10 months ago
Background Modeling for Segmentation of Video-Rate Stereo Sequences
Stereo sequences promise to be a powerful method for segmenting images for applications such as tracking human figures. We present a method of statistical background modeling for ...
Christopher K. Eveland, Kurt Konolige, Robert C. B...
TIP
2008
344views more  TIP 2008»
13 years 8 months ago
A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications
Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being...
Lucia Maddalena, Alfredo Petrosino
CVPR
2012
IEEE
11 years 11 months ago
Adaptive object tracking by learning background context
One challenge when tracking objects is to adapt the object representation depending on the scene context to account for changes in illumination, coloring, scaling, etc. Here, we p...
Ali Borji, Simone Frintrop, Dicky N. Sihite, Laure...
EVOW
2010
Springer
13 years 12 months ago
Towards Automated Learning of Object Detectors
Recognizing arbitrary objects in images or video sequences is a difficult task for a computer vision system. We work towards automated learning of object detectors from video seque...
Marc Ebner