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Headprint – Person Reacquisition Using Visual Features of Hair in Overhead Surveillance Video

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Audio- and Video-Based Biometric Person Authentication (AVBPA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3546))

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Abstract

In this paper, we present the results of our investigation of the use of the visual characteristics of human hair as a primary recognition attribute for human ID in indoor video imagery. The emerging need for unobtrusive biometrics has led to recent research interest in using the features of the face, gait, voice, and clothes, among others, for human authentication. However, the characteristics of hair have been almost completely excluded as a recognition attribute from state-of-the-art authentication methods. We contend that people often use hair as a principal visual biometric. Furthermore, hair is the part of the human body most likely to be visible to overhead surveillance cameras free of occlusion. Although hair can hardly be trusted to be a reliable long-term indicator of human identity, we show that the visual characteristics of hair can be effectively used to unobtrusively re-establish human ID in the task of short-term recognition and reacquisition in a video-based multiple-person continuous tracking application. We propose new pixel-based and line-segment-based features designed specifically to characterize hair, and recognition schemes that use just a few training images per subject. Our results demonstrate the feasibility of this approach, which we hope can form a basis for further research in this area.

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© 2005 Springer-Verlag Berlin Heidelberg

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Aradhye, H., Fischler, M., Bolles, R., Myers, G. (2005). Headprint – Person Reacquisition Using Visual Features of Hair in Overhead Surveillance Video. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_92

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  • DOI: https://doi.org/10.1007/11527923_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27887-0

  • Online ISBN: 978-3-540-31638-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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