A Review of Content-Based Video Retrieval Techniques for Person Identification


  • Syahmi Syahiran Ahmad Ridzuan School of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia.
  • Zaid Omar Department of Electric and Computer Engineering, School of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  • Usman Ullah Sheikh Department of Electric and Computer Engineering, School of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia




Clothing Recognition, Content-Based Video Retrieval, Ethnic Recognition, Gender Recognition, Person Identification.


The rise of technology spurs the advancement in the surveillance field. Many commercial spaces reduced the patrol guard in favor of Closed-Circuit Television (CCTV) installation and even some countries already used surveillance drone which has greater mobility. In recent years, the CCTV Footage have also been used for crime investigation by law enforcement such as in Boston Bombing 2013 incident. However, this led us into producing huge unmanageable footage collection, the common issue of Big Data era. While there is more information to identify a potential suspect, the massive size of data needed to go over manually is a very laborious task. Therefore, some researchers proposed using Content-Based Video Retrieval (CBVR) method to enable to query a specific feature of an object or a human. Due to the limitations like visibility and quality of video footage, only certain features are selected for recognition based on Chicago Police Department guidelines. This paper presents the comprehensive reviews on CBVR techniques used for clothing, gender and ethnic recognition of the person of interest and how can it be applied in crime investigation. From the findings, the three recognition types can be combined to create a Content-Based Video Retrieval system for person identification.


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How to Cite

Ahmad Ridzuan, S. S., Omar, Z., & Sheikh, U. U. (2019). A Review of Content-Based Video Retrieval Techniques for Person Identification. ELEKTRIKA- Journal of Electrical Engineering, 18(3), 49–56. https://doi.org/10.11113/elektrika.v18n3.196