K-means Tracking with Variable Ellipse Model

• Item type: Trans(1)
• 公開日: 2005-10-15
• タイトル: K-means Tracking with Variable Ellipse Model
• タイトル / 言語: en
• タイトル: K-means Tracking with Variable Ellipse Model
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 一般・研究論文
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Wakayama University
• 著者所属: Wakayama University
• 著者所属: Wakayama University
• 著者所属: Wakayama University
• 著者所属(英): en
• 著者所属(英): Wakayama University
• 著者所属(英): en
• 著者所属(英): Wakayama University
• 著者所属(英): en
• 著者所属(英): Wakayama University
• 著者所属(英): en
• 著者所属(英): Wakayama University
• 著者名: Chunsheng, Hua; Haiyuan, Wu; Toshikazu, Wada; Qian, Chen
• 著者名(英): Chunsheng, Hua; Haiyuan, Wu; Toshikazu, Wada; Qian, Chen
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: We have proposed a K-means clustering based target tracking method compared with the template matching which can work robustly when tracking an object with hole through which the background can be seen (e.g. mosquito coil) (hereafter we call this problem as the background interfusion or the interfused background).This paper presents a new method for solving the drawbacks of the previous method i.e. low speed instability caused by the change of shape and size. Our new tracking model consists of a single target center and a variable ellipse model for representing non-target pixels. The contributions of our new method are: 1) The original K-means clustering is replaced by a 2_*-means clustering and the non-target cluster center is adaptively picked up from the pixels on the ellipse. This modification reduces the number of distance computation and improves the stability of the target detection as well. 2) The ellipse parameters are adaptively adjusted according to the target detection result. This adaptation improves the robustness against the scale and shape changes of the target. Through the various experiments we confirmed that our new method improves speed and robustness of our original method.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: We have proposed a K-means clustering based target tracking method, compared with the template matching, which can work robustly when tracking an object with hole through which the background can be seen (e.g., mosquito coil) (hereafter we call this problem as the background interfusion or the interfused background).This paper presents a new method for solving the drawbacks of the previous method, i.e., low speed, instability caused by the change of shape and size. Our new tracking model consists of a single target center, and a variable ellipse model for representing non-target pixels. The contributions of our new method are: 1) The original K-means clustering is replaced by a 2_*-means clustering, and the non-target cluster center is adaptively picked up from the pixels on the ellipse. This modification reduces the number of distance computation and improves the stability of the target detection as well. 2) The ellipse parameters are adaptively adjusted according to the target detection result. This adaptation improves the robustness against the scale and shape changes of the target. Through the various experiments, we confirmed that our new method improves speed and robustness of our original method.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11560603
• 書誌情報: 情報処理学会論文誌コンピュータビジョンとイメージメディア（CVIM）; 巻 46, 号 SIG15(CVIM12), p. 59-68, 発行日 2005-10-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7810
• 出版者 / 言語: ja
• 出版者: 情報処理学会