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.
This project is funded in part by ETRI OCR and in part by the Korea Research Foundation Grant funded by the Korean Government(MOEHRD)(KRF-2006-612-D00081).
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Lee, W., Woo, W., Boyer, E. (2007). Identifying Foreground from Multiple Images. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4844. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76390-1_57
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DOI: https://doi.org/10.1007/978-3-540-76390-1_57
Publisher Name: Springer, Berlin, Heidelberg
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