Target tracking in infrared imagery using a novel particle filter
To address two challenging problems in infrared target tracking, target appearance changes and unpredictable abrupt motions, a novel particle filtering based tracking algorithm is introduced. In this method, a novel saliency model is proposed to distinguish the salient target from background, and the eigenspace model is invoked to adapt target appearance changes. To account for the abrupt motions efficiently, a two-step sampling method is proposed to combine the two observation models. The proposed tracking method is demonstrated through two real infrared image sequences, which include the changes of luminance and size, and the drastic abrupt motions of the target.
刘尔琦：Institute of the Second Academy, China Aerospace Science and Industry Corporation, Beijing 100854, China
杨杰：Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China
郁生阳：Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China
周越：Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China
备注：The authors are thankful to Xiaodi Hou for his valuable discussion and the centre of imaging science, ARO DAAH049510494 for providing the AMCOM infrared data sets. This work was supported by the National “863" Project of China (No. 2007AA01Z164) and the National Natural Science Foundation of China (Nos. 60675023 and 60602012).
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