An appearance-based approach to assistive identity inference using LBP and colour histograms

Authors:
Sareh Abolahrari Shirazi;Farhad Dadgostar;Brian C. Lovell
Affiliations:
NICTA, QLD, Australia and The University of Queensland, School of ITEE, QLD, Australia;NICTA, QLD, Australia and The University of Queensland, School of ITEE, QLD, Australia;NICTA, QLD, Australia and The University of Queensland, School of ITEE, QLD, Australia
Venue:
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Year:
2010

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Abstract

Robust identity inference is one of the biggest challenges in current visual surveillance systems. Although, face is an important biometric for generic identity inference, it is not always accessible in video-based surveillance systems due to the poor quality of the video or ineffective viewpoints where the captured face is not clearly visible. Hence, taking advantage of additional features to increase the accuracy and reliability of these systems is an increasing need. Appearance and clothing are potentially suitable for visual identification and tracking suspects. In this research we present a novel approach for recognition of upper body clothing, using local binary patterns (LBP) and colour information, as an assistive tool for identity inference.