Image difference threshold strategies and shadow detection
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of Moving Shadows using Mean Shift Clustering and a Significance Test
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Moving Shadow Detection with Support Vector Domain Description in the Color Ratios Space
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
Robust and Efficient Foreground Analysis for Real-Time Video Surveillance
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Moving Cast Shadow Detection from a Gaussian Mixture Shadow Model
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Shadow detection for moving objects based on texture analysis
Pattern Recognition
Learning and Removing Cast Shadows through a Multidistribution Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Detect Moving Shadows in Dynamic Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient background subtraction and shadow removal for monochromatic video sequences
IEEE Transactions on Multimedia - Special section on communities and media computing
Detection of moving cast shadows for object segmentation
IEEE Transactions on Multimedia
Moving Cast Shadows Detection Using Ratio Edge
IEEE Transactions on Multimedia
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient moving object segmentation algorithm using background registration technique
IEEE Transactions on Circuits and Systems for Video Technology
Insignificant shadow detection for video segmentation
IEEE Transactions on Circuits and Systems for Video Technology
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Motion detection algorithms usually detect moving regions in a rough way; in some application contexts it could be mandatory to obtain the exact shape of such objects by removing cast shadows as well as ghosts and reflections due to variations in light conditions. To address this problem we propose an approach based on edge matching. The basic idea is that edges extracted in shadow (or ghost) regions in current image exactly match with edges extracted in the correspondent regions in the background image. On the contrary, edges extracted on foreground objects have not correspondent edges in the background image. In order to remove all shadow regions instead of only shadow points, we firstly segment the foreground image into subregions, according to uniformity of photometric gain between adjacent points. The algorithm has been tested in many different real contexts, both in indoor and outdoor environments.