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It has some advantages of low cost, small memory, and good tracking effect. However, there are some shortcomings in the existing algorithm; for example, it cannot produce adaptive changes as the target size changes. And when there are similar objects, it is prone to target positioning errors and tracking failures caused by occlusion. In this paper, an improved method of continuous adaptive change Mean shift (Camshift) for high-precision positioning and tracking is proposed. The traditional Camshift method only uses hue components in HSV to extract features. This paper uses the combination of H and S components in HSV space to build a two-dimensional color feature histogram and with the image\u2019s LBP feature histogram to increase tracking accuracy. Meanwhile, for the sake of target occlusion and nonlinear changes in the tracking process, this paper introduces a Gaussian-Hermit particle filter that is updated by the Kalman filter. Experimental result demonstrates that the real-time performance of the proposal in this paper is better than Mean shift, Camshift, simple particle filter, and Kalman filter.<\/jats:p>","DOI":"10.1155\/2020\/8846977","type":"journal-article","created":{"date-parts":[[2020,11,26]],"date-time":"2020-11-26T02:35:06Z","timestamp":1606358106000},"page":"1-13","source":"Crossref","is-referenced-by-count":3,"title":["Implementation of Camshift Target Tracking Algorithm Based on Hybrid Filtering and Multifeature Fusion"],"prefix":"10.1155","volume":"2020","author":[{"given":"Sijie","family":"Du","sequence":"first","affiliation":[{"name":"Shandong Key Laboratory for Normal Distributed Computer Software Technology, School of Physics and Electronic Science, Shandong Normal University, Jinan 250014, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxin","family":"Xu","sequence":"additional","affiliation":[{"name":"Shandong Key Laboratory for Normal Distributed Computer Software Technology, School of Physics and Electronic Science, Shandong Normal University, Jinan 250014, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6710-9436","authenticated-orcid":true,"given":"Tianping","family":"Li","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Science, Shandong Normal University, Jinan 250014, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"issue":"1-2","key":"1","first-page":"119","article-title":"Modified Kalman filtering framework based real time target tracking against environmental dynamicity in wireless sensor networks","volume":"40","author":"S. 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