Title :
Detection and tracking of a moving point target in infrared image sequence using auxiliary particle filter
Author :
Liu, Zhijun ; Xie, Shengli ; Ren, Xianyi
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou
Abstract :
An appropriate measurement likelihood function is proposed from the measurement image model employed by most of the track-before-detect (TBD) approaches. Based on the likelihood function and a target motion model, we design an auxiliary particle filter-based Bayes multiframe method for detection and tracking a moving point target in infrared (IR) image sequences. Experimental results show its effectiveness for the detection and tracking of a low signal-to-noise ratio (SNR) point target.
Keywords :
Bayes methods; image motion analysis; image sequences; infrared imaging; object detection; particle filtering (numerical methods); target tracking; Bayes multiframe method; appropriate measurement likelihood function; auxiliary particle filter; infrared image sequences; likelihood function; moving point target detection; moving point target tracking; signal-to-noise ratio; track-before-detect approaches; Clutter; Image sequences; Infrared detectors; Infrared imaging; Machine learning; Matched filters; Particle filters; Particle tracking; Radar tracking; Target tracking; Infrared image; Particle filter; Point targets; Tracking;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620834
