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Scientific Publications

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Abstract

In spite of the increasing concerns raised by privacy advocates against the intrusive deployment of large scale surveillance cameras, the research community has progressed with a remarkable pace into the area of smart visual surveillance. The automation for surveillance systems becomes an obligation to avoid human errors and ensure an efficient strategy for tackling crimes and preventing further terrorist attacks. In this research article, we survey the recent studies in computer vision on gait recognition for covert identification and its application for surveillance scenarios and forensic investigation. The integration of biometric technologies into surveillance systems is a major step milestone to improve the automation process in order to recognize criminal offenders and track them across different places. The suitability of gait biometrics for surveillance applications emerges from the fact that the walking pattern can be captured and perceived from a distance even with poor resolution video as opposed to other biometric modalities which their performance deteriorates in surveillance scenarios.

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