Title of Paper:Continuously Adaptive Mean-shift Tracking Algorithm with Suppressed Background Histogram Model

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Affiliation of Author(s):电子信息工程学院

Journal:Dianzi Yu Xinxi Xuebao

Abstract:For the deficiency of traditional Continuously Adaptive Mean-shift (CAMshift) tracking algorithm can easily contain a large number of color information which belongs to the background in the process of establishing the target color model, an improved algorithm is proposed. The original image is divided into foreground and background based on the Gaussian Mixture Model(GMM). In the original image and the background image, the histogram of the hue component is established. Hue histograms of the background image are used to calculate the weight of the hue component in the original image. The hues belonging to the background are suppressed and the color differences between foreground and background are expanded. Experiment shows that by suppressing the hue components belonging to the background, the saliency of the target color model is expanded. The accuracy and stability of the target recognition are improved. The ratio of the max deviation to the target is less than 20%, which ensures the target not to be lost. © 2019, Science Press. All right reserved.

ISSN No.:1009-5896

Translation or Not:no

Date of Publication:2019-06-01

Co-author:Wang, Yiwei,YAN HE

Correspondence Author:wxd