ISCAS OpenIR
一种尺度自适应的Mean Shift跟踪算法
Alternative TitleMean shift tracking algorithm with scale adaptation
张凤军; 赵岭; 安国成; 王宏安; 戴国忠; Zhang, F.(zhaoling@ict.ac.cn)
2014
Source计算机研究与发展
ISSN10001239
Volume51Issue:1Pages:215-224
English Abstract针对传统Mean Shift中跟踪窗口尺度不能实时适应跟踪目标变化这一问题,提出一种基于图割理论的Mean Shift尺度自适应算法.根据每一帧图像的Mean Shift迭代结果,在其周围的一个小区域内,利用先验的肤色混合高斯模型构造图并建立关于标号的能量模型,使用max flow/min cut算法计算出能量函数最小值实现图割,在图割后的肤色团块中寻找最大团判定为跟踪目标,并以该团的尺度来实时调整目标跟踪窗口.实验结果表明,该方法 克服了缩放10%核带宽的经典尺度适应方法的带宽趋于缩小问题,实时地反映跟踪目标真实尺度变化,避免背景中其他目标的干扰,具有较好的实用性和鲁棒性, 而且可以应用到娱乐游戏控制中,丰富人机交互操作方式.
Indexed TypeEI ; CSCD
AbstractThis paper presents an adaptive window object tracking method for Mean Shift based on graph cuts theory. It copes with the size-changing object during visual tracking while the traditional Mean Shift can't change the scale of tracking window in real time. According to the Mean Shift iteration result of every frame, graph is created by using skin color Gaussian mixture model in a small area around it. Graph cut is implemented by calculating the minimum energy function based on max flow/min cut principle. And then the largest skin lump is found, which is accepted as tracking object in the result of graph cuts. As a result, tracking window size can be updated by the largest skin lump. Experimental results clearly demonstrate that the method can avoid the problem of nonstop shrinking bandwidth effectively which is brought by expanding and shrinking 10% of kernel function bandwidth. It reflects the real scale change of tracking target in real time, avoids the interference of other targets in the background, and has good usability and robustness. Besides it can be applied to controlling entertainment games that enriches operation mode of human computer interaction.
Keyword图割理论 均值移动 尺度自适应 跟踪 人机交互
Department张凤军, 中国科学院软件研究所人机交互技术与智能信息处理实验室, 北京 100190, 中国. 赵岭, 中国科学院软件研究所人机交互技术与智能信息处理实验室, 北京 100190, 中国. 安国成, 中国科学院软件研究所人机交互技术与智能信息处理实验室, 北京 100190, 中国. 王宏安, 中国科学院软件研究所人机交互技术与智能信息处理实验室, 北京 100190, 中国. 戴国忠, 中国科学院软件研究所人机交互技术与智能信息处理实验室, 北京 100190, 中国.
Language中文
CSCD IDCSCD:5046672
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/16770
Collection中国科学院软件研究所
Corresponding AuthorZhang, F.(zhaoling@ict.ac.cn)
Recommended Citation
GB/T 7714
张凤军,赵岭,安国成,等. 一种尺度自适应的Mean Shift跟踪算法[J]. 计算机研究与发展,2014,51(1):215-224.
APA 张凤军,赵岭,安国成,王宏安,戴国忠,&Zhang, F..(2014).一种尺度自适应的Mean Shift跟踪算法.计算机研究与发展,51(1),215-224.
MLA 张凤军,et al."一种尺度自适应的Mean Shift跟踪算法".计算机研究与发展 51.1(2014):215-224.
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