Abstract
A static binocular camera system is widely used in many computer vision applications; and being able to segment foreground, shadow, and background is an important problem for them. In this paper, we propose a homography-correspondence pair-based segmentation framework. Existing segmentation approaches, based on homography constraints, often suffer from occlusion problems. In our approach, we treat a homography-correspondence pair symmetrically, to explicitly take the occlusion relationship into account, and we regard the segmentation problem as a multi-labeling problem for the homography-correspondence pair. We then formulate an energy function for this problem and get the pair-wise segmentation results by minimizing them via an α-β swap algorithm. Experimental results show that accurate segmentation is obtained in the presence of the occlusion region in each side image.
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Iwama, H., Makihara, Y., Yagi, Y. (2011). Foreground and Shadow Segmentation Based on a Homography-Correspondence Pair. In: Kimmel, R., Klette, R., Sugimoto, A. (eds) Computer Vision – ACCV 2010. ACCV 2010. Lecture Notes in Computer Science, vol 6495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19282-1_56
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DOI: https://doi.org/10.1007/978-3-642-19282-1_56
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