On Using High-Definition Body Worn Cameras for Face Recognition from a Distance

  • Wasseem Al-Obaydy
  • Harin Sellahewa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6583)


Recognition of human faces from a distance is highly desirable for law-enforcement. This paper evaluates the use of low-cost, high-definition (HD) body worn video cameras for face recognition from a distance. A comparison of HD vs. Standard-definition (SD) video for face recognition from a distance is presented. HD and SD videos of 20 subjects were acquired in different conditions and at varying distances. The evaluation uses three benchmark algorithms: Eigenfaces, Fisherfaces and Wavelet Transforms. The study indicates when gallery and probe images consist of faces captured from a distance, HD video result in better recognition accuracy, compared to SD video. This scenario resembles real-life conditions of video surveillance and law-enforcement activities. However, at a close range, face data obtained from SD video result in similar, if not better recognition accuracy than using HD face data of the same range.


HD video Face Recognition Face Database Surveillance Eigenfaces Fisherfaces Wavelet Transforms 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Wasseem Al-Obaydy
    • 1
  • Harin Sellahewa
    • 1
  1. 1.Department of Applied ComputingUniversity of BuckinghamBuckinghamUK

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