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Copyright of Journal of Mechanical Strength / Jixie Qiangdu is the property of Zhengzhou Research Institute of Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Preventive Veterinary Medicine / Zhongguo Yufang Shouyi Xuebao is the property of Chinese Journal of Preventive Veterinary Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Modern Laboratory Medicine is the property of Journal of Modern Laboratory Medicine Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problems of that the detecting module scans a large number of sub windows, which results the detection time is too long, and when the target has serious occlusion and deformation during the tracking process, the traditional tracking learning detection (TLD) target tracking algorithm will fail to track, so this paper proposed the improved TLD target tracking algorithm. Before the detection module, it added the ViBe model to estimate the foreground target. which greatly reduced the detection area. The tracking module used the SIFT feature matching algorithm to replace the optical flow method in the original algorithm, accurately tracked the target to avoid the tracking drift, reduced the complexity of the calculation and improved the ability of the algorithm to adapt to the environment. The experiment results show that the improved TLD algorithm can improve the running speed, and the tracking accuracy can also be improved when the target is seriously occluded and the light intensity changes dramatically. [ABSTRACT FROM AUTHOR]