Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios

Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering ”a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in ...

• Type: Conference
• Year: 2009
• Where: ICCV
• Authors: Ivan Huerta, Michael Holte, Thomas Moeslund, and Jordi Gonzàlez
• Keywords: Background Subtraction, Colour Segmentation, Computer Vision, Edge Segmentation, ICCV 2009, Image Processing, Motion Segmentation, Shadows, Temporal Difference, Video Surveillance.