Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/1571
Title: Cyclic motion detection for motion based recognition
Authors: Kasparis, Takis 
Tsai, PingSing 
Shah, Mubarak A. 
metadata.dc.contributor.other: Κασπαρής, Τάκης
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Computer vision;Pattern recognition;Equations of motion
Issue Date: Dec-1994
Source: Pattern Recognition, 1994, vol. 27, no.12, pp. 1591-1603
Volume: 27
Issue: 12
Start page: 1591
End page: 1603
Journal: Pattern Recognition 
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: https://hdl.handle.net/20.500.14279/1571
ISSN: 00313203
DOI: 10.1016/0031-3203(94)90079-5
Rights: © Elsevier
Type: Article
Affiliation: University of Central Florida 
Affiliation : University of Central Florida 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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