Call for Papers for the Special Issue of The Machine Vision and Applications Journal on Video Surveillance Research in Industry and Academia Aims and Scope The surge in the global need for automated and reliable security and surveillance systems has elicited a significant response from both industry and academia in the domain of video analysis based sensing, processing and decision support. Computer vision research and development has advanced the state-of-the-art in video surveillance related algorithms in conjunction with the exploitation of increasing processing power of standard computing platforms for deployed and experimental systems. The surge in startup companies devoted to various aspects of video surveillance systems as well as the substantial increase in government funding for related advanced development have helped achieve a high level of maturity in various aspects of the field. This special Issue of MVA aims to showcase recent advances in video surveillance, with emphasis on state-of-the-art systems and technologies both in industry and academia. This single issue with a representation of applied technologies and state-of-the-art algorithms from both practitioners and researchers will help practicing engineers, active researchers, faculty and students alike in getting to know the current status and open problems. We solicit papers that will capture the depth and breadth of the state of the art in video surveillance. The papers should be based on algorithms and systems that have been proven to be robust and reliable in real-world settings by demonstrating that significant evaluation has been done either on real data or in real-world deployed environments. Submissions are solicited in, but not limited to, the following areas: (1) Applications of video surveillance technology – This will include the use of various computer vision techniques such as object detection, tracking, recognition and event detection in different applications. Papers devoted to multi-camera scenarios, large area surveillance under varying environmental and geometric constraints, and to complex environments such as airports and similar locales are especially encouraged. (2) Review papers – Researchers interested in video surveillance, both beginners and experts alike, will benefit from comprehensive reviews of existing work in specific areas. Especially relevant are reviews that can present a critique of existing algorithms by relying on analysis as well as significant amount of experimental evidence. (3) Algorithm evaluations – Evaluation of state-of-the-art computer vision algorithms in terms of their accuracy, robustness, and efficiency. These studies are crucial for people who are interested in building real computer vision products. (4) New algorithms – Provocative novel ideas that have the potential of spawning novel research and bringing a paradigmatic shift are always welcome in this rapidly progressing area. For algorithm evaluations, the datasets are required to be shared online to facilitate future comparisons and critiques. For papers proposing new algorithms, demonstrating both the strengths and weaknesses of the algorithms will help practitioners to appreciate the work in a more accurate way. Guest Editors Prof. Hai Tao, University of California, Santa Cruz, CA, tao@soe.ucsc.edu Dr. Harpreet Singh Sawhney, Sarnoff Corporation, NJ, hsawhney@sarnoff.com Key Dates Full paper submission deadline April 15, 2006 Notification ofacceptance July 1, 2006 Camera-ready manuscript due August 15, 2006 Web Links Online submission: http://mc.manuscriptcentral.com/mva. Special issue home page: http://www.soe.ucsc.edu/~tao/mva ________________________________________ ~Sheli Carr Editorial Coordiator Machine Vision and Applications Journal Office: (407) 823-6495 Fax: (407) 823-0594