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  • 标题:Tracking High Speed Skater by Using Multiple Model
  • 本地全文:下载
  • 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.
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