Object tracking of Ochotona curzoniae based on local texture difference operator

doi:10.6041/j.issn.1000-1298.2015.05.004

	Object tracking of Ochotona curzoniae based on local texture difference operator
	Chen, Haiyan 1,2; Zhang, Aihua 1; Hu, Shiya 1
刊名	Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
	2015-05-25
卷号	46 期号:5 页码:20-25
关键词	Color Ecosystems Textures Tracking (position) Color information Difference operators Mean shift Mean shift algorithm Mean-shift tracking Object Tracking Ochotona curzoniae Target and background
ISSN号	10001298
DOI	10.6041/j.issn.1000-1298.2015.05.004
英文摘要	In order to accurately track Ochotona curzoniae in natural habitat environment, an object tracking method based on Meanshift algorithm was proposed. Considering the object tracking method of kernel Meanshift algorithm based on RGB color histogram usually has the deformation of inaccurate tracking or lose of target in the scenario that the color is similar between the background and the object. In view of the problem that the color between the Ochotona curzoniae and the background is similar in the object tracking process in natural habitat environment, a visual descriptor named as the local texture difference operator (LTDC) was proposed to reflect the subtle differences between the Ochotona curzoniae and background. The LTDC operator was combined with color information to characterize the object model and the object model was embedded into the Meanshift tracking framework for the object tracking of Ochotona curzoniae. The experimental results show that the proposed method for characterizing the object has a strong difference ability of target and background. The object can be accurately positioned in the color similar scenario of the object and the background. Compared with the FLBP algorithm, the average iteration number of proposed method is 79.04% of the average iteration number of the FLBP algorithm, the average tracking total time of proposed method is 82.35% of the average tracking total time of the FLBP algorithm, the average tracking speed of proposed method is 1.22 times of the average tracking speed of the FLBP algorithm. ©, 2015, Chinese Society of Agricultural Machinery. All right reserved.
语种	中文
出版者	Chinese Society of Agricultural Machinery
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/112811]
专题	计算机与通信学院电气工程与信息工程学院
作者单位	1.College of Electronic and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China; 2.School of Computer and Communication, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Chen, Haiyan,Zhang, Aihua,Hu, Shiya. Object tracking of Ochotona curzoniae based on local texture difference operator[J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery,2015,46(5):20-25.
APA	Chen, Haiyan,Zhang, Aihua,&Hu, Shiya.(2015).Object tracking of Ochotona curzoniae based on local texture difference operator.Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery,46(5),20-25.
MLA	Chen, Haiyan,et al."Object tracking of Ochotona curzoniae based on local texture difference operator".Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery 46.5(2015):20-25.