IMAGE SEQUENCE MEASURES FOR AUTOMATIC TARGET TRACKING

被引:12
|
作者
Diao, W. -H. [1 ,2 ]
Mao, X. [1 ]
Zheng, H. -C. [1 ]
Xue, Y. -L. [1 ]
Gui, V. [3 ]
机构
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China
[2] China Acad Space Technol, Inst Manned Spacecraft Syst Engn, Beijing 100094, Peoples R China
[3] Politehn Timisoara Univ, Fac Elect & Telecommun, Timisoara 300223, Romania
关键词
HUMAN DETECTION PERFORMANCE; CLUTTER; RECOGNITION; ALGORITHM; METRICS; PROBABILITY;
D O I
10.2528/PIER12050810
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the field of automatic target recognition and tracking, traditional image metrics focus on single images, ignoring the sequence information of multiple images. We show that measures extracted from image sequences are highly relevant concerning the performances of automatic target tracking algorithms. To compensate the current lack of image sequence characterization systems from the perspective of the target tracking difficulties, this paper proposes three new metrics for measuring image sequences: inter-frame change degree of texture, inter-frame change degree of target size and inter-frame change degree of target location. All are based on the fact that inter-frame change is the main cause interfering with target tracking in an image sequence. As image sequences are an important type of data in the field of automatic target recognition and tracking, it can be concluded that the work in this paper is a necessary supplement for the existing image measurement systems. Experimental results reported show that the proposed metrics are valid and useful.
引用
收藏
页码:447 / 472
页数:26
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