Detection and tracking of a moving point target in infrared image sequence using auxiliary particle filter
Zhijun Liu, Sheng-Li Xie, Xianyi Ren · 2008
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.