Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Removal of Shadows from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Detect Moving Shadows in Dynamic Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
ETISEO, performance evaluation for video surveillance systems
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
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Several video-based applications, such as video surveillance, traffic monitoring, video annotation, etc., rely on the correct detection and tracking of moving objects within the observed scene. Even though several works have been proposed in the field of moving object detection, many of them do not consider the problem of segmenting real objects from their shadows. The shadow is considered part of the object, thus leading to possibly large errors in the subsequent steps of object localisation and tracking. In this paper we propose a shadow detection algorithm able to remove shadows from the blobs of moving objects, using division images and Expectation-Maximization histogram analysis. Experimental results prove that the use of the proposed method can significantly increase the performance of a video analysis system.