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