Picture-in-picture copy detection using spatial coding techniques

  • Authors:

  • Sanjay Purushotham;Qi Tian;C.-C. Jay Kuo

  • Affiliations:

  • University of Southern California, Los Angeles, CA, USA;University of Texas at San Antonio, San Antonio, TX, USA;University of Southern California, Los Angeles, CA, USA

  • Venue:
  • AIEMPro '11 Proceedings of the 2011 ACM international workshop on Automated media analysis and production for novel TV services
  • Year:
  • 2011

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Abstract

Picture-in-Picture (PiP) is a special video transformation where one or more videos is scaled and spatially embedded in a host video. PiP is a very useful service to watch two or more videos simultaneously, however it can be exploited to visually hide one video inside another video. Today's copy detection techniques can be easily fooled by PiP, which is reflected in the poor results in the yearly TRECVID competitions. Inspired by the promise of spatial coding in partial image matching, we propose a generalized spatial coding representation in which both the relative position and relative orientation is embedded in the spatial code. In this paper, we will provide novel formulation for spatial verification problem and introduce polynomial and non-polynomial algorithms to efficiently address the spatial verification problem. Our initial experiment results on TRECVID and MSRA datasets shows that our proposed spatial verification algorithms provide around 20% improvement over the classical hierarchical bag-of-words approach.