文章基本信息

标题：Tracking High Speed Skater by Using Multiple Model
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作者：GuoJun Liu ; XiangLong Tang
期刊名称：Computer and Information Science
印刷版ISSN：1913-8989
电子版ISSN：1913-8997
出版年度：2009
卷号：2
期号：1
页码：126
DOI：10.5539/cis.v2n1P126
语种：English
出版社：Canadian Center of Science and Education
摘要：Normal 0 7.8 ? 0 2 false false false MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:????; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} Color-based tracking is a very popular technique for object tracking. However, under varying environmental conditions in video sequences, the existing tracking methods tend to be unreliable for tracking high speed objects. It is possible under such a complex environment that the targets may disappear totally or partially due to occlusion. To over this problem, a novel approach of multiple-color model is proposed in this paper. Different colors extracted from the skater’s head and body are tracked with Kalman filter, respectively. A confidence measure representing the reliability of each color tracking result is presented to guide possible re-detection for continuous tracking. Experimental results show that the proposed approach is very efficient and effective in tracking high-speed skater in real short track sequences.