Abstract
In this paper we explore a multi-layer background change detection method based on projections of spatiotemporal 3D texture maps. The aim of this method is to provide a background change detection of a region viewed by multiple cameras. Camera views are projected onto a common ground plane, thus creating a spatially aligned multi-layer background. The aligned multi-layer background is subdivided into non-overlapping texture blocks, and block data is dimensionally reduced by principal component analysis. Motion detection is performed on each block, and non-moving sections of the block are clustered into multiple hyperspheres. An analysis of the clusters from spatially aligned multi-layer blocks reveal regions of changed background. This method is evaluated on surveillance videos available from PETS2006 and PETS2007 datasets.
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Miezianko, R., Pokrajac, D. (2009). Multi-layer Background Change Detection Based on Spatiotemporal Texture Projections. In: Bolc, L., Kulikowski, J.L., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2008. Lecture Notes in Computer Science, vol 5337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02345-3_28
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DOI: https://doi.org/10.1007/978-3-642-02345-3_28
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