Recent research activities in videosurveillance at UNIFI:MICC

Abstract: Recently, image quality validation has been largely investigated to increase recognition rates and to support decisions of authentication systems. This may be useful to alarm a video surveillance application for a particular intrusion event and requires also the system to work at frame rate. We present a technique for detecting and tracking several targets in real-time, also exploiting a simple data association method to prevent two or more tracker from latching onto the same face and consequently invalidating the collected data for each target. Quantitative results show that the proposed approach makes it possible to acquire face images and evaluate their quality so as to build a complete and concise log for each intrusion event.

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