Video event detection as matching of spatiotemporal projection

  • Authors:
  • Dong-Jun Park;David Eichmann

  • Affiliations:
  • Institute for Clinical and Translational Sciences, The University of Iowa, Iowa City, IA;Institute for Clinical and Translational Sciences, The University of Iowa, Iowa City, IA

  • Venue:
  • ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
  • Year:
  • 2010

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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.