针对目前运动目标跟踪算法的计算结果和效率不能令人满意的现状,提出利用改进的Hausdorff距离进行模板匹配,它具有计算量小,适应性强的特点.为了能较快的跟踪目标,采用多分辨率分析的方法处理序列图像.实验结果表明,本文的算法能显著提高运动目标跟踪的准确程度和效率.
参考文献
[1] | Huttenlocher D P, Klanderman G A, Ruchlidge W J. Comparing image using the Hausdorff distance [J]. IEEETran PAMI, 1993, 15(9): 850-863. |
[2] | Meier Thomas, Ngan King N. Automatic segmentation of moving objects for video object plane generation [J].IEEE Transactions on Circuits and Systems for Video Technology, 1998, (5): 525-540. |
[3] | Know Oh-Kyn, Sim Dong-gyn, Park Rae-Hong. Robust Hausdorff distance matching algorithms using Pyramidal structures [J]. Pattern Recognition, 2001, 34(7): 2005-2013. |
[4] | Sim D G, Kwon O K, Park R H. Object matching algorithm using robust Hausdorff distance measures [J]. IEEE Trans. Image Process, 1999, 8(2): 425-429. |
[5] | Borgerfors G. Distance transformations in digital images [J]. CVGIP, 1986, 34(3): 344-371. |
[6] | Canny J A. Computational approach to edge detection [J]. IEEE Tran PAMI, 1986, 8(6): 679-697. |
[7] | Liu Ke, Zhang Xianmin, Fu Yonghui. Tracking object using improved Hausdorff measure [J]. Journal of Shanghai Jiaotong University(上海交通大学学报),2001,35(2):223-227.(in Chinese). |
[8] | Han Jun, Xiong Zhang, Sun Wenyan, et al. A Method for implementation of automatic segmenting and tracking of video moving objects[J].Journal of Image and Graphics(中国图象图形学报),2001,6(8):732-738(in Chinese). |
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