Title :
Occlusion resistant object tracking
Author :
Loutas, E. ; Diamantaras, K. ; Pitas, I.
Author_Institution :
Dept. of Informatics, Thessaloniki Univ., Greece
Abstract :
Object tracking with occlusion prediction using multiple feature correspondences is proposed. The tracking region is defined by a set of point features, tracked using Kanade-Lucas-Tomasi (1991) algorithm. During total occlusion the region position is estimated using motion prediction based on a Kalman filtering scheme applied to the motion model prior to occlusion. During partial occlusion the displacements of the occluded features are predicted based on the motion of the bounding box of the moving object. Experimental results on real and artificial images have shown that the algorithm behaves well under total and partial occlusion
Keywords :
Kalman filters; computer graphics; feature extraction; filtering theory; motion estimation; prediction theory; tracking; Kanade-Lucas-Tomasi algorithm; artificial images; bounding box motion; motion model; multiple feature correspondences; occlusion prediction; occlusion resistant object tracking; partial occlusion; point features; real images; region position estimation; total occlusion; tracking region; Educational technology; Equations; Filtering; Image sequences; Informatics; Kalman filters; Motion estimation; Predictive models; Robustness; Target tracking;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.958425