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像素点特征加权的尺度自适应跟踪算法 被引量：3

Pixel feature-weighted scale-adaptive object tracking algorithm
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摘要 针对目标运动过程中的姿态变化、旋转、干扰以及缩放等情况,提出了结合像素点特征加权的尺度自适应跟踪算法。首先利用目标区域中每个像素点的颜色特征和位置特征,建立目标模型;其次用目标的平均权值图估算尺度变化系数,以实现目标尺度的自适应;最后构建一个更新模型,对跟踪过程中的目标模型和背景模型进行更新。实验表明,提出的算法充分利用目标区域内各像素点间的差异,可以做到快速、有效的跟踪,且具有较强的顽健性。 An effective object tracking method using weighted pixel features was proposed to deal with all kinds of complicated tracking situations, such as target movement, rotation, background interference and scaling and so on. First, the color feature and location information of the pixels in the target area were used to build the object model. Then the average weight image was used to estimate the scale variation coefficient. The aim was to adapt to the scale changes of the target. Finally, an update model was proposed, which was able to renew the object model and background model. The experimental results show that the proposed algorithm could make full use of the differences between pixels in the target area, so it can track more quickly and more effectively with strong robustness.
作者 罗会兰 杜芳芳 孔繁胜
机构地区 江西理工大学信息工程学院 浙江大学计算机科学技术学院
出处 《通信学报》 EI CSCD 北大核心 2015年第10期200-210,共11页 Journal on Communications
基金 国家自然科学基金资助项目(61105042 61462035) 江西省教育厅科技基金资助项目(GJJ13421)~~
关键词 目标跟踪 尺度自适应 更新模型 像素点特征加权 object tracking scale-adaptive model updating pixel weighted-feature
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献16

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共引文献9

同被引文献22

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引证文献3

二级引证文献12

通信学报
2015年 第10期

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