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Analyzing and Recognizing Pedestrian Motion Using 3D Sensor Network and Machine Learning

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Web, Artificial Intelligence and Network Applications (WAINA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 927))

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Abstract

How to analyze and recognize pedestrian movements is an important issue dependent on motion capture devices. In our work, we used two types of popular 3D sensors such as 3D depth sensor and 3D motion sensor to construct a sensor network for tacking motion of target because of their convenience and low cost. In this paper, we first describe how to get data from the sensor network and how to process raw data. Next, we provide algorithms for applying machine learning to the analysis and recognition of human motions. Finally, we give some evaluation experimental results.

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References

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Author information

Authors and Affiliations

  1. Department of Human-Oriented Information System Engineering, National Institute of Technology, Kumamoto College, 2659-2 Suya, Koshi, Kumamoto, 861-1102, Japan

    Ningping Sun

  2. Advanced Electronics and Information Systems Engineering Course, National Institute of Technology, Kumamoto College, 2659-2 Suya, Koshi, Kumamoto, 861-1102, Japan

    Toru Tsuruoka, Shunsuke Murakami & Takuma Sakamoto

Authors
  1. Ningping Sun
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  2. Toru Tsuruoka
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  3. Shunsuke Murakami
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  4. Takuma Sakamoto
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Corresponding author

Correspondence to Ningping Sun .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Advanced Sciences, Hosei University, Koganei-Shi, Tokyo, Japan

    Makoto Takizawa

  3. Department of Computer Science, Technical University of Catalonia, Barcelona, Barcelona, Spain

    Fatos Xhafa

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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© 2019 Springer Nature Switzerland AG

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Sun, N., Tsuruoka, T., Murakami, S., Sakamoto, T. (2019). Analyzing and Recognizing Pedestrian Motion Using 3D Sensor Network and Machine Learning. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_15

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