VFerret: Content-based similarity search tool for continuous archived video

Zhe Wang, Matthew D. Hoffman, Perry R. Cook, Kai Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

This paper describes VFerret, a content-based similarity search tool for continuous archived video. Instead of depending on attributes or annotations to search desired data from long-time archived video, our system allows users to perform content-based similarity search using visual and audio features, and to combine content-based similarity search with traditional search methods. Our preliminary experience and evaluation shows that content-based similarity search is easy to use and can achieve 0.79 average precision on our simple benchmark. The system is constructed using Ferret toolkit and its memory footprint for metadata is small, requiring about 1.4Gbytes for one year of continuous archived video data.

Original languageEnglish (US)
Title of host publicationProceedings of the 3rd ACM Workshop on Continuous Archival and Retrieval of Personal Experiences, CARPE'06
Pages19-25
Number of pages7
DOIs
StatePublished - 2006
Event3rd ACM Workshop on Continuous Archival and Retrieval of Personal Experiences, CARPE'06 - Santa Barbara, CA, United States
Duration: Oct 23 2006Oct 27 2006

Publication series

NameProceedings of the 3rd ACM Workshop on Continuous Archival and Retrievalof Personal Experiences, CARPE'06

Other

Other3rd ACM Workshop on Continuous Archival and Retrieval of Personal Experiences, CARPE'06
Country/TerritoryUnited States
CitySanta Barbara, CA
Period10/23/0610/27/06

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Software

Keywords

  • Similarity search
  • Video retrieval

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