Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/7212
Title: Cyclic motion detection for motion based recognition
Authors: Kasparis, Takis 
Tsai, PingSing
Shah, Mubarak A.
Keywords: Computer vision;Pattern recognition;Equations of motion
Issue Date: 1994
Publisher: Pergamon
Source: Pattern Recognition, 1994, Volume 27, Issue 12, Pages 1591-1603
Abstract: The motion of a walking person is analyzed by examining cycles in the movement. Cycles are detected using autocorrelation and Fourier transform techniques of the smoothed spatio-temporal curvature function of trajectories created by specific points on the object as it performs cyclic motion. A large impulse in the Fourier magnitude plot indicates the frequency at which cycles are occurring. Both synthetically generated and real walking sequences are analyzed for cyclic motion. The real sequences are then used in a motion based recognition application in which one complete cycle is stored as a model, and a matching process is performed using one cycle of an input trajectory.
URI: http://ktisis.cut.ac.cy/handle/10488/7212
http://ktisis.cut.ac.cy/handle/10488/7212
http://hdl.handle.net/10488/7212
ISSN: 00313203
DOI: http://dx.doi.org/10.1016/0031-3203(94)90079-5
Rights: © 1994 Pattern Recognition Societ
Type: Article
Appears in Collections:Άρθρα/Articles

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