Abstract In this paper, we present a novel foreground extraction method that automatically identifies image regions corresponding to a common space region seen from multiple cameras. We assume that background regions present some color coherence in each image and we exploit the spatial consistency constraint that several image projections of the same space region must satisfy. Integrating both color and spatial consistency constraints allows to fully automatically segment foreground and background regions in multiple images. In contrast to standard background subtraction approaches, the proposed approach does not require any a priori knowledge on the background nor user interactions. We demonstrate the effectiveness of the method for multiple camera setups with experimental results on standard real data sets.
Identifying Foreground from Multiple Images
Computer Vision – ACCV 2007 ; 8 ; 580-589
Lecture Notes in Computer Science ; 4844 , 8
2007-01-01
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Multiple Image , Visual Hull , Foreground Region , Spatial Consistency , Foreground Extraction Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence (incl. Robotics) , Biometrics , Algorithm Analysis and Problem Complexity
Foreground Focus: Unsupervised Learning from Partially Matching Images
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