Title

Cyclic motion detection for motion based recognition

Keywords

Cyclic motion; Motion-based recognition; Spatio-temporal curvature

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. © 1994.

Publication Date

1-1-1994

Publication Title

Pattern Recognition

Volume

27

Issue

12

Number of Pages

1591-1603

Document Type

Article

Identifier

scopus

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/0031-3203(94)90079-5

Socpus ID

0028727096 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0028727096

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