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Journal of Flow Visualization and Image Processing
SJR: 0.11 SNIP: 0.312 CiteScore™: 0.1

ISSN 印刷: 1065-3090
ISSN オンライン: 1940-4336

Journal of Flow Visualization and Image Processing

DOI: 10.1615/JFlowVisImageProc.2017018183
pages 69-92

IMAGE PROCESSING IN VISUAL TRACKING BY VARIOUS TECHNIQUES WITH THE USE OF A PARTICLE FILTER − A CRITICAL REVIEW

Xiang Xuezhi
College of Information & Communication Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, P.R. China
Syed Masroor Ali
College of Information & Communication Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, PR China
Ghulam Farid
College of Information & Communication Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, P.R. China
Muhammad Bilal
College of Information & Communication Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, P.R. China

要約

Image processing is an inevitable tool for visual tracking. Visual object tracking is a very hot area of research in computer vision. Different techniques have been developed for object tracking. Objects in nonlinear motion are tracked by using a particle filter (PF). The particle filter has been used in various fields and applications efficiently and prominently. In this paper, it is shown in which way spatial, color, and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter-like mechanism with many other methodologies. It is also emphasized how the PF is helpful for other natural systems such as bird flocks, fish schools, and insects worms consisting of a huge group of moving individuals. It is illustrated that particle filter in combination with numerous other techniques is one of the algorithm that can be instrumental in localization of objects even if they are in 2D or 3D shape from motion. This paper also represents the way in which PF can be used on the pixel level only from a static camera. In this paper, many other techniques are discussed to indicate their effectiveness with PF.


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