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A scene-adaptive motion detection model based on machine learning and data clustering

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Abstract

Due to its wide applications and importance in computer vision, motion detection has been receiving considerable attention from industry and academy. However, previous motion detection algorithms fail to achieve the flexibility and accuracy simultaneously for good detection results. In the present work, a scene-adaptive motion detection model based on machine learning and clustering technology is proposed. This model begins with training to the system by a group of testing images, in terms of various accurate parameters of one certain scene. Significant modifications have been reserved in the same area during motion detection, which are considered as a change clustering. Then, the model takes advantage of clustering technology to generate a minimum spanning tree (MST), which is one kind of average linkage clustering. The average shortest distance of the minimum spanning tree serves as a benchmark to identify the change in images. Finally the training parameters and detection algorithm are combined to monitor the scene. The clustering is introduced to this model during sample training, in order to obtain factors of higher quality followed by more accurate detection results. Finally, the experiment confirms the excellent adaptability and precision of the proposed motion detection model.

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Acknowledgments

This work was financially supported by the Program of Education Commission of Hubei Province, China (Grant No.Q20131904), the National Natural Science Foundation of China (Grant No. 61261016), the National Culture Promotion Project of China (Grant No.201307)and the Program of Ethnic and Religious Affairs Commission of Hubei Province, China (Grant No.HBMW2012006). Moreover, during the research, many valuable suggestions have been provided by Professor May Huang and Dr. Eric Chen, International Technological University, USA.

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Authors and Affiliations

  1. School of Information Engineering, Hubei University for Nationalities, Enshi, Hubei, China

    Tao Hu, Minghui Zheng, Jun Li & Li Zhu

  2. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, L16 9JD, UK

    Jia Hu

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  1. Tao Hu
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  2. Minghui Zheng
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  3. Jun Li
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  4. Li Zhu
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Correspondence to Minghui Zheng.

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Hu, T., Zheng, M., Li, J. et al. A scene-adaptive motion detection model based on machine learning and data clustering. Multimed Tools Appl 74, 2821–2839 (2015). https://doi.org/10.1007/s11042-013-1741-0

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