IMAGE SEQUENCE MEASURES FOR AUTOMATIC TARGET TRACKING
Author(s) -
Wei-He Diao,
Xia Mao,
Haichao Zheng,
Yuli Xue,
Vasile Gui
Publication year - 2012
Publication title -
electromagnetic waves
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 89
eISSN - 1559-8985
pISSN - 1070-4698
DOI - 10.2528/pier12050810
Subject(s) - artificial intelligence , sequence (biology) , computer vision , computer science , tracking (education) , image (mathematics) , pattern recognition (psychology) , biology , genetics , psychology , pedagogy
In the fleld 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 di-culties, 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 fleld 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.
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