Abstract
Removing shadows casted by moving foreground objects in a scene is a critical problem for many vision-based applications. We propose two algorithms that examine color/texture invariants, and exploit spatial-temporal consistency to detect shadows efficiently and reliably. The first algorithm assumes a static background model while the second algorithm addresses the perturbations of dynamic background in natural scenes. The experimental results show that the proposed methods can detect penumbra as well as umbra in different kinds of scenarios under various illumination conditions.
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© 2006 Springer-Verlag Berlin Heidelberg
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Lo, KH., Yang, MT., Lin, RY. (2006). Shadow Removal for Foreground Segmentation. In: Chang, LW., Lie, WN. (eds) Advances in Image and Video Technology. PSIVT 2006. Lecture Notes in Computer Science, vol 4319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949534_34
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DOI: https://doi.org/10.1007/11949534_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68297-4
Online ISBN: 978-3-540-68298-1
eBook Packages: Computer ScienceComputer Science (R0)