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基于CamShift的自适应颜色空间目标跟踪算法 被引量:22

Object tracking algorithm with adaptive color space based on CamShift
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摘要 CamShift算法只适于特定颜色目标的跟踪,针对这一不足,提出了自适应颜色空间目标跟踪算法。依据当前测量值,根据类间平均距离动态选择当前颜色空间。颜色空间更新判断机制的引入,降低了颜色空间更新带来的时间开销。实验结果表明,该算法可以更准确地在复杂背景下的跟踪各种色彩的目标。 Considering the poor performance that CamShift algorithm only applies to track targets with certain color,an improved algorithm named adaptive color space tracking algorithm was proposed.Using the new measurements,the current color space was selected dynamically according to the average distance between objects and backgrounds.With the introduction of the mechanism in similarity analysis,time cost was decreased.The experimental results show the new algorithm can track multi-color targets in complex backgrou...
出处 《计算机应用》 CSCD 北大核心 2009年第3期757-760,共4页 journal of Computer Applications
基金 陕西省自然科学基金资助项目(2007E229)
关键词 目标跟踪 连续自适应均值漂移算法 颜色空间选择 object tracking continuously adaptive mean shift color space model selection
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  • 1[1]Fukanaga K, Hostetler LD. The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Trans. on Information Theory, 1975,21(1):32-40.
  • 2[2]Cheng Y. Mean shift, mode seeking and clustering. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1995,17(8):790-799.
  • 3[3]Comaniciu D, Ramesh V, Meer P. Real-Time tracking of non-rigid objects using mean shift. In: Werner B, ed. IEEE Int'l Proc. of the Computer Vision and Pattern Recognition, Vol 2. Stoughton: Printing House, 2000. 142-149.
  • 4[4]Yilmaz A, Shafique K, Shah M. Target tracking in airborne forward looking infrared imagery. Int'l Journal of Image and Vision Computing, 2003,21 (7):623-635.
  • 5[5]Bradski GR. Computer vision face tracking for use in a perceptual user interface In: Regina Spencer Sipple, ed. IEEE Workshop on Applications of Computer Vision. Stoughton: Printing House, 1998. 214-219.
  • 6[6]Comaniciu D, Ramesh V, Meer P. Kernel-Based object tracking. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2003,25(5):564-575.
  • 7[7]Collins RT. Mean-Shift blob tracking through scale space. In: Danielle M, ed. IEEE Int'l Conf. on Computer Vision and Pattern Recognition, Vol 2. Baltimore: Victor Graphics, 2003. 234-240.
  • 8[8]Olson CF. Maximum-Likelihood image matching. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2002,24(6):853-857.
  • 9[9]Hu W, Wang S, Lin RS, Levinson S. Tracking of object with SVM regression. In: Jacobs A, Baldwin T, eds. IEEE Int'l Conf. on Computer Vision and Pattern Recognition, Vol 2. Baltimore: Victor Graphics, 2001. 240-245.
  • 10[10]Mohammad GA. A fast globally optimal algorithm for template matching using low-resolution pruning. IEEE Trans. on Image Processing, 2001,10(4):626-533.

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