Smart cameras enabling automated face recognition in the crowd for intelligent surveillance system

Smart Cameras are rapidly finding their way into Intelligent Surveillance Systems. Recognizing faces in the crowd in real-time is one of the key features that will significantly enhance Intelligent Surveillance Systems. The main challenge is the fact that the enormous volumes of data generated by high-resolution sensors can make it computationally impossible to process on mainstream processors. In this paper we report on the prototyping development of a smart camera for automated face recognition using very high resolution sensors. In the proposed technique, the smart camera extracts all the faces from the full-resolution frame and only sends the image information from these face areas to the main processing unit — vastly reducing data rates. Face recognition software that runs on the main processing unit will then perform the required pattern recognition. BIOGRAPHY: Y. M. Mustafah is a PhD student of The University of Queensland. His research interest is in face detection and recognition and embedded systems for computer vision. A. Bigdeli is a researcher of SAFE Sensors group in National ICT Australia. His main research is in high performance real-time embedded systems for computer vision applications. A. W. Azman is also a PhD student of The University of Queensland. Her research interest is in the softwarehardware partitioning on embedded system and embedded systems for computer visions. B. C. Lovell is a Professor in School of ITEE, The University of Queensland. He is also the research leader of the SAFE Sensors group in National ICT Australia. His main interest is the analysis of video streams for human activities recognition.