%0 Journal Article
%T Chromatic shadow detection and tracking for moving foreground segmentation
%A Ivan Huerta
%A Michael Holte
%A Thomas B. Moeslund
%A Jordi Gonzalez
%J Image and Vision Computing
%D 2015
%V 41
%F Ivan Huerta2015
%O ISE; 600.078; 600.063
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2703), last updated on Thu, 21 Jan 2016 16:05:45 +0100
%X Advanced segmentation techniques in the surveillance domain deal with shadows to avoid distortions when detecting moving objects. Most approaches for shadow detection are still typically restricted to penumbra shadows and cannot cope well with umbra shadows. Consequently, umbra shadow regions are usually detected as part of moving objects, thus aecting the performance of the nal detection. In this paper we address the detection of both penumbra and umbra shadow regions. First, a novel bottom-up approach is presented based on gradient and colour models, which successfully discriminates between chromatic moving cast shadow regions and those regions detected as moving objects. In essence, those regions corresponding to potential shadows are detected based on edge partitioning and colour statistics. Subsequently (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for each potential shadow region for detecting the umbra shadow regions. Our second contribution renes even further the segmentation results: a tracking-based top-down approach increases the performance of our bottom-up chromatic shadow detection algorithm by properly correcting non-detected shadows.To do so, a combination of motion lters in a data association framework exploits the temporal consistency between objects and shadows to increasethe shadow detection rate. Experimental results exceed current state-of-the-art in shadow accuracy for multiple well-known surveillance image databases which contain dierent shadowed materials and illumination conditions.
%K Detecting moving objects
%K Chromatic shadow detection
%K Temporal local gradient
%K Spatial and Temporal brightness and angle distortions
%K Shadow tracking
%U http://refbase.cvc.uab.es/files/HHM2015.pdf
%U http://dx.doi.org/10.1016/j.imavis.2015.06.003
%P 42-53