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

  • Ningping SunEmail author
  • Toru Tsuruoka
  • Shunsuke Murakami
  • Takuma Sakamoto
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 927)

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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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ningping Sun
    • 1
    Email author
  • Toru Tsuruoka
    • 2
  • Shunsuke Murakami
    • 2
  • Takuma Sakamoto
    • 2
  1. 1.Department of Human-Oriented Information System EngineeringNational Institute of Technology, Kumamoto CollegeKoshiJapan
  2. 2.Advanced Electronics and Information Systems Engineering CourseNational Institute of Technology, Kumamoto CollegeKoshiJapan

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