Abstract
Detection of events and actions in video entails substantial processing of very large, even open-ended, video streams. Video data presents a unique challenge for the information retrieval community because it is hard to find a way to properly represent video events. We propose a novel approach to analyze temporal aspects of video data. We consider the video data as a sequence of images that form a 3-dimensional spatiotemporal structure, and multiview orthographic projection is performed to transform the video data into 2-dimensional representations. The projected views allow a unique way to represent video events, and we apply template matching using color moments to detect video events.
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Park, DJ., Eichmann, D. (2010). Video Event Detection as Matching of Spatiotemporal Projection. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17277-9_15
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DOI: https://doi.org/10.1007/978-3-642-17277-9_15
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