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A motion classification model with improved robustness through deformation code integration

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Abstract

During data acquisition, samples in a time series may contain noise, such as inconsistent data ranges, inconsistent data, and incomplete data. Therefore, the classification model requires improved robustness to correctly classify the sequence of human motion. This paper presents a classification model with improved robustness performance based on the factored gated restricted Boltzmann machine to effectively overcome the various aforementioned data problems. The proposed model acquires the deformation code of each action first and integrates the deformation codes together to be an integrated deformation code of the entire sequence. Then, the model determines the classification from the integrated deformation code. This approach mainly focuses on the deformation relations among action samples in the extraction sequence, and it ignores the data expression in the sequence samples. Experiments show that the proposed model performs better than state-of-the-art approaches in terms of the robustness of time series classification with noise.

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Acknowledgements

This work was supported by the National Science Foundation of China (Grant No. 61625204), partially supported by the State Key Program of National Science Foundation of China (Grant No. 61432012 and 61432014).

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Authors and Affiliations

  1. The Machine Intelligence Laboratory, Computer Science College, Sichuan University, China, No. 24 South Section 1, Yihuan Road, Chengdu, 610005, Sichuan, China

    Lei Xia, Jiancheng Lv & Dongbo Liu

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  1. Lei Xia
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  2. Jiancheng Lv
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  3. Dongbo Liu
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Correspondence to Jiancheng Lv.

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We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work and that there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, “A Motion Classification Model with Improved Robustness through Deformation Code Integration.”

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Xia, L., Lv, J. & Liu, D. A motion classification model with improved robustness through deformation code integration. Neural Comput & Applic 31, 8519–8532 (2019). https://doi.org/10.1007/s00521-018-3681-0

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