DocumentCode :
3020892
Title :
Non-linear IR Scene Prediction for Range Video Surveillance
Author :
Celenk, Mehmet ; Graham, James ; Cheng, Kai-Jen
Author_Institution :
Ohio Univ., Athens
fYear :
2007
fDate :
17-22 June 2007
Firstpage :
1
Lastpage :
6
Abstract :
This paper describes a non-linear IR (infra-red) scene prediction method for range video surveillance and navigation. A Gabor-filter bank is selected as a primary detector for any changes in a given IR range image sequence. The detected ROI (region of interest) involving arbitrary motion is fed to a non-linear Kalman filter for predicting the next scene in time-varying 3D IR video. Potential applications of this research are mainly in indoor/outdoor heat-change based range measurement, synthetic IR scene generation, rescue missions, and autonomous navigation. Experimental results reported herein show that non-linear Kalman filtering-based scene prediction can perform more accurately than linear estimation of future frames in range and intensity driven sensing. The low least mean square error (LMSE), on the average of about 2% using a bank of 8 Gabor filters, also proves the reliability of the IR scene estimator (or predictor) developed in this work.
Keywords :
Gabor filters; Kalman filters; image motion analysis; least mean squares methods; video surveillance; Gabor-filter bank; IR range image sequence; arbitrary motion; autonomous navigation; heat-change based range measurement; least mean square error; nonlinear IR scene prediction; nonlinear Kalman filter; range video surveillance; region of interest; Gabor filters; Image sequences; Infrared detectors; Infrared surveillance; Kalman filters; Layout; Motion detection; Navigation; Prediction methods; Video surveillance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
ISSN :
1063-6919
Print_ISBN :
1-4244-1179-3
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2007.383445
Filename :
4270443
Link To Document :
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