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Style of Action based Individual Recognition in Video Sequences.

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Yogarajah, Pratheepan, Prasad, G and Condell, J (2008) Style of Action based Individual Recognition in Video Sequences. In: The IEEE 2008 International Conference on Systems, Man and Cybernetics (SMC 2008), Suntec Singapore International Convention Exhibition Centre, Singapore. UNSPECIFIED. 6 pp. [Conference contribution]

Full text not available from this repository.

URL: http://ieeexplore.ieee.org/search/srchabstract.jsp?arnumber=4811452&isnumber=4811240&punumber=4803719&k2dockey=4811452@ieeecnfs&query=%28+%28%28prasad++g.%29%3Cin%3Eau+%29+%29+%3Cand%3E+%28pyr+%3E%3D+2008+%3Cand%3E+pyr+%3C%3D+2010%29&pos=8&access=no

DOI: 10.1109/ICSMC.2008.4811452

Abstract

We present a method for recognizing individuals from their ldquostyle of actionrdquo. Two forms of human recognition can be useful: the determination that an object is from the class of humans (which is called human detection), and the determination that an object is a particular individual from this class (this is called individual recognition). This paper focuses on the latter problem. A periodicity is detected in from a sequence of motion detected binary image frames by finding the maximum similarity measure between them. Based on the periodicity information the Motion History Image (MHI) is applied for each individual sequence to find out entire motion information of periodic action. The individual is then recognized using a partial Hausdorff Distance similarity measure and the SVM classification approach.

Item Type:Conference contribution (Poster)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:8895
Deposited By:Professor Girijesh Prasad
Deposited On:01 Feb 2010 12:19
Last Modified:22 Jul 2011 15:42

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