Vision & Cognition Laboratory

Department of Computer Science, Drexel University

 
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Illumination Eigenspace and Shadow Removal

Cast shadows produce troublesome effects for video surveillance systems. To robustly eliminate these shadows from image sequences as a preprocessing stage for robust video surveillance, we propose a framework based on the idea of intrinsic images. Unlike previous methods to derive intrinsic images, we derive time-varying reflectance images and corresponding illumination images from a sequence of images. Using the illumination images, we normalize the input image sequence in terms of distribution of the incident lighting to eliminate shadow effects. We also propose an approach which can potentially run in realtime by introducing illumination eigenspace, which captures the illumination variation due to weather, time of day, etc., and a shadow interpolation method based on shadow hulls. (with Y. Matsushita and K. Ikeuchi)

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