Computer Science ›› 2016, Vol. 43 ›› Issue (3): 291-295.doi: 10.11896/j.issn.1002-137X.2016.03.054

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Non-parametric Dynamic Background Modeling Based on Direction Feature of Vector

JIANG Yong-sen, XIAO Quan and WANG Shou-jue   

  • Online:2018-12-01 Published:2018-12-01

Abstract: For the problem that the traditional background modeling results in empty hole and wrong shadow detection,we proposed a dynamic background modeling method based on vector characteristics.Learning algorithm is divided into two parts namely initial background model and updating background model.The initial background model maps the RGB feature to the direction feature in spherical coordinates.K clustering centers are calculated by the lastest images using the method of mean vector clustering algorithm,and the K clusters are considered to be the background model of the pixel.When a new image’s corresponding pixel falls into any one of the K clusters,the new pixel is considered to be background.The updating algorithm is the successor of the initial background model algorithm.Besides doing background analyse for the new image,it also uses the new image to update the background model.The algorithm can effectively reduce the empty hole and wrong shadow detection,and can update the background timely when the scene changes.

Key words: Vector direction feature,Background modeling,Mean vector clustering,Update background

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