Forensic video reconstruction

  • Authors:
  • Larry Huston;Rahul Sukthankar;Jason Campbell;Padmanabhan Pillai

  • Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • Proceedings of the ACM 2nd international workshop on Video surveillance & sensor networks
  • Year:
  • 2004

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Abstract

This paper describes an application that enables quick reconstruction of interconnected events, sparsely captured by one or more surveillance cameras. Unlike related efforts, our approach does not require indexing, advance knowledge of potential search criteria, nor a solution to the generalized object-recognition problem. Instead, we strategically pair the intelligence and skill of a human investigator with the speed and flexibility of a parallel image search engine that exploits local storage and processing capabilities distributed across large collections of video recording devices. The result is a system for fast, interactive, brute-force video searching which is both effective and highly scalable.