Zhang, LingZhu, YaoLiao, BinXiao, ChunxiaJernej Barbic and Wen-Chieh Lin and Olga Sorkine-Hornung2017-10-162017-10-1620161467-8659https://doi.org/10.1111/cgf.13278https://diglib.eg.org:443/handle/10.1111/cgf13278Shadow removal for videos is an important and challenging vision task. In this paper, we present a novel shadow removal approach for videos captured by free moving cameras using illumination transfer optimization. We first detect the shadows of the input video using interactive fast video matting. Then, based on the shadow detection results, we decompose the input video into overlapped 2D patches, and find the coherent correspondences between the shadow and non-shadow patches via discrete optimization technique built on the patch similarity metric. We finally remove the shadows of the input video sequences using an optimized illumination transfer method, which reasonably recovers the illumination information of the shadow regions and produces spatio-temporal shadow-free videos. We also process the shadow boundaries to make the transition between shadow and non-shadow regions smooth. Compared with previous works, our method can handle videos captured by free moving cameras and achieve better shadow removal results. We validate the effectiveness of the proposed algorithm via a variety of experiments.Computing methodologiesCollision detectionHardwareSensors and actuatorsPCB design and layout10.1111/cgf.13278125-134