title: Improved infrared target-tracking algorithm based on mean shift.
abstract: An improved IR target-tracking algorithm based on mean shift is proposed herein, which combines the mean-shift-based gradient-matched searching strategy with a feature-classification-based tracking algorithm. An improved target representation model is constructed by considering the likelihood ratio of the gray-level features of the target and local background as a weighted value of the original kernel histogram of the target region. An expression for the mean-shift vector in this model is derived, and a criterion for updating the model is presented. Experimental results show that the algorithm improves the shift weight of the target pixel gray level and suppresses background disturbance.
authors.affiliation: Research Center for Space Optical Engineering, Harbin Institute of Technology, Harbin, China. wangzhile_hit@163.com
authors.forename: Zhile
authors.initials: Z
authors.lastname: Wang
authors.forename: Qingyu
authors.initials: Q
authors.lastname: Hou
authors.forename: Ling
authors.initials: L
authors.lastname: Hao