CYCLIC MOTION DETECTION FOR MOTION BASED RECOGNITION

The motion of a walking person is analyzed by examining cycles in the movement. Cycles are detected using autocorrelation and Fourier transf orm techniques of the smoothed spatio-temporal curvature function of t rajectories created by specific points on the object as it performs cy clic motion. A large impulse in the Fourier magnitude plot indicates t he frequency at which cycles are occurring. Both synthetically generat ed 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.