Learning an intrinsic-variable preserving manifold for dynamic visual tracking

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
Hong QiaoSuiwu Zheng

Abstract

Manifold learning is a hot topic in the field of computer science, particularly since nonlinear dimensionality reduction based on manifold learning was proposed in Science in 2000. The work has achieved great success. The main purpose of current manifold-learning approaches is to search for independent intrinsic variables underlying high dimensional inputs which lie on a low dimensional manifold. In this paper, a new manifold is built up in the training step of the process, on which the input training samples are set to be close to each other if the values of their intrinsic variables are close to each other. Then, the process of dimensionality reduction is transformed into a procedure of preserving the continuity of the intrinsic variables. By utilizing the new manifold, the dynamic tracking of a human who can move and rotate freely is achieved. From the theoretical point of view, it is the first approach to transfer the manifold-learning framework to dynamic tracking. From the application point of view, a new and low dimensional feature for visual tracking is obtained and successfully applied to the real-time tracking of a free-moving object from a dynamic vision system. Experimental results from a dynamic tracking system whi...Continue Reading

References

Dec 23, 2000·Science·J B TenenbaumJ C Langford
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Jun 6, 2007·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Liang Wang, David Suter

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Citations

Nov 20, 2012·Annual Review of Pathology·Farzad GhaznaviMichael Feldman
Jan 22, 2015·IEEE Transactions on Neural Networks and Learning Systems·Shenglan LiuHong Qiao
Jul 17, 2014·IEEE Transactions on Cybernetics·Tianxiang BaiXiaolong Zhou
Oct 21, 2014·IEEE Transactions on Cybernetics·Tianyu YangMax Q-H Meng
Jun 13, 2013·IEEE Transactions on Cybernetics·Zulfiqar Hasan Khan, Irene Yu-Hua Gu
May 20, 2014·IEEE Transactions on Cybernetics·Junqiu Wang, Yasushi Yagi
Jun 28, 2012·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Hong QiaoBo Zhang
Sep 20, 2011·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Shiming XiangChangshui Zhang
Jul 15, 2015·IEEE Transactions on Cybernetics·Luming ZhangYingjie Xia
May 26, 2017·IEEE Transactions on Neural Networks and Learning Systems·Shihui YingHong Qiao
Jul 11, 2018·IEEE Transactions on Cybernetics·Xiao SunZhenguang Liu
Oct 7, 2017·International Journal of Neural Systems·Xin LiShihui Ying

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