Study on intelligent automatic tracking of moving targets in image sequences = 영상 신호를 이용한 움직이는 표적의 지능적인 자동 추적에 관한 연구

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Several algorithms have been developed for the tracking of a moving target in image sequences. In these tracking algorithms, a centroid tracking algorithm and a correlation tracker are the most popular ones. The centroid tracker determines a target aim point by computing the geometric or intensity centroid of the target object based on the target segmentation method. In the correlation tracker, the motion of a block of pixels, termed a reference block, is estimated by looking for the most similar block of pixels in the subsequent frames. This dissertation studies on new automatic tracking algorithms of moving targets in image sequences, which include an intelligent centroid tracking algorithm and a robust correlation tracker. The performance of the centroid tracker depends on the following factors: (1) efficient real-time preprocessing technique, (2) exact segmentation algorithm, and (3) intelligent control of a tracking window size, etc.. Previous segmentation algorithms for the centroid tracker utilize only an intensity feature to segment a moving target from background images. And, they assume that all the related probability density functions of the target and the background are Gaussian ones in most cases. Ordinary segmentation algorithms often produce unstable results in real unconstrained outdoor scenes. In real tracking environments, the assumed Gaussian pdf`s are very different from those of real image sequences. Thus, it may be almost impossible to extract the target exactly from the cluttered image sequences. This dissertation proposes an efficient real-time preprocessing method in order to enhance the distinction between the objects of interest and their local backgrounds. In addition, a real-time adaptive segmentation method based on new distance features is also proposed for the intelligent centroid tracker. The novel features include spatial distances between the predicted center pixel of a target from a tracking filter and each pixel for the...
Advisors
Park, Dong-Joresearcher박동조researcher
Description
한국과학기술원 : 전기및전자공학전공,
Publisher
한국과학기술원
Issue Date
2001
Identifier
165643/325007 / 000965386
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 전기및전자공학전공, 2001.2, [ xv, 195 p. ]

Keywords

Selective attention; Robust correlation tracker; Intelligent centroid tracker; Video target tracker; Intelligent target segmentation; 지능적인 표적 분리; 선택적 집중도; 강인한 상관 방식 추적기; 지능적인 표적 중심 추적기; 영상 표적 추적기

URI
http://hdl.handle.net/10203/35889
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=165643&flag=dissertation
Appears in Collection
EE-Theses_Ph.D.(박사논문)
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