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基于改进李群结构的特征协方差目标跟踪
Target tracking with feature covariance based on an improved Lie Group structure

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李广伟 1   刘云鹏 1   尹健 2   史泽林 1  
文摘 最近的研究发现,在对称正定流形上可构造一种改进的李群结构,并赋予具有双不变度量性质的对数-欧几里得黎曼度量,所得到的距离公式和黎曼均值均呈现简单形式.据此,利用目标的综合特征构建区域协方差阵为目标建模,提出一种基于改进李群结构的特征协方差目标跟踪方法.实验表明,这种跟踪方法实用有效,在相同的条件下,因为算法的计算量的减少,跟踪性能略优于基于仿射黎曼度量的协方差目标跟踪.
其他语种文摘 Recent research shows that an improved Lie group structure can be constructed on the symmetric positive manifold. This will lead to a bi-invariant log-Euclidean metric, which makes the distance formula and Riemannian mean take a much simpler form. We model the tracked object with its covariance feature of the interest region and propose a feature covariance tracking method based on the improved Lie group structure. Experimental results show that this method is practical and efficient. Under the same tracking condition, its performance is slightly superior to that of the method based on widely used affine invariant Riemannian metric.
来源 仪器仪表学报 ,2010,31(1):111-116 【核心库】
关键词 目标跟踪 ; 特征协方差 ; 李群 ; 黎曼流形 ; 指数映射
地址

1. 中国科学院沈阳自动化研究所, 辽宁, 沈阳, 110016  

2. 空军装备研究院总体所, 北京, 100076

语种 中文
文献类型 研究性论文
ISSN 0254-3087
学科 自动化技术、计算机技术
基金 国家自然科学基金
文献收藏号 CSCD:3828405

参考文献 共 13 共1页

1.  ZHOU S K. Visual tracking and recognition using appearance adaptive models in particle filters. IEEE Transactions on Image Processing,2004,13(11):1491-1506 被引 36    
2.  刘良江. 灰度直方图和支持向量机在磁环外观检测中的应用. 仪器仪表学报,2006,27(8):840-844 被引 6    
3.  HAGER G D. Efficient region tracking with parametric models of geometry and illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence,1998,20(10):1025-1039 被引 33    
4.  BAKER S. Lucas-Kanade 20 years on:A unifying framework. International Journal of Computer Vision,2004,56(3):221-255 被引 147    
5.  ROSS D. Incremental learning for robust visual tracking. International Journal of Computer Vision,2008,77(1/3):125-141 被引 367    
6.  LI X. Robust visual tracking based on incremental tensor subspace learning. Proceeding of the IEEE International Conference on Computer Vision,2007 被引 1    
7.  TUZEL O. Region covariance:A fast descriptor for detection and classification. Proceeding of 9th European Conference on Computer Vision,2006:589-600 被引 3    
8.  PENNEC X. A Riemannian framework for tensor computing. International Journal of Computer Vision,2006,66(1):41-66 被引 50    
9.  PORIKLI F. Covariance tracking using model update based on Riemannian manifolds. Proceeding of IEEE Conference on Computer Vision and Pattern Recognition,2006:728-735 被引 2    
10.  ARSIGNY V. Geometric means in a novel vector space structure on symmetric positive-definite matrices. SIAM Journal on Matrix Analysis and Applications,2006,29(1):328-347 被引 23    
11.  HALL S B. Lie algebras,and Representations:an Elementary Introduction,2003 被引 1    
12.  HELGASON S. Differential geometry,Lie Groups,and symmetric spaces,1978 被引 7    
13.  CHRISTOPHE L. Statistics on the manifold of multivariate normal distribution:theory and application to diffusion tensor MRI processing[Technical Report RR-5242],2004 被引 1    
引证文献 7

1 李广伟 基于黎曼二阶最小化的投影图像配准算法* 仪器仪表学报,2010,31(6):1323-1329
被引 1

2 樊振华 采用激活区域场景分析的红外目标跟踪算法 计算机辅助设计与图形学学报,2011,23(10):1741-1748
被引 2

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