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Activity Recognition from Trajectory Data

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Computing with Spatial Trajectories

Abstract

In today's world, we have increasingly sophisticated means to record the movement of humans and other moving objects in the form of trajectory data. These data are being accumulated at an extremely fast rate. As a result, knowledge discovery from these data for recognizing activities has become an important problem. The discovered activity patterns can help us understand people's lives, analyze traffic in a large city and study social networks among people. Trajectory-based activity recognition builds upon some fundamental functions of location estimation and machine learning, and can provide new insights on how to infer high-level goals and objectives from low-level sensor readings. In this chapter, we survey the area of trajectory-based activity recognition. We start from research in location estimation from sensors for obtaining the trajectories. We then review trajectory-based activity recognition research. We classify the research work on trajectory-based activity recognition into several broad categories, and systematically summarize existing work as well as future works in light of the categorization.

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Authors and Affiliations

  1. Hong Kong University of Science and Technology, Hong Kong, China

    Yin Zhu, Vincent Wenchen Zheng & Qiang Yang

Authors
  1. Yin Zhu
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  2. Vincent Wenchen Zheng
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  3. Qiang Yang
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Corresponding author

Correspondence to Yin Zhu .

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Editors and Affiliations

  1. Microsoft Research Asia, Beijing, 100080, China, People's Republic

    Yu Zheng

  2. , School of Information Technology, University of Queensland, Brisbane, 4072, Queensland, Australia

    Xiaofang Zhou

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Zhu, Y., Zheng, V.W., Yang, Q. (2011). Activity Recognition from Trajectory Data. In: Zheng, Y., Zhou, X. (eds) Computing with Spatial Trajectories. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1629-6_6

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  • DOI: https://doi.org/10.1007/978-1-4614-1629-6_6

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  • Print ISBN: 978-1-4614-1628-9

  • Online ISBN: 978-1-4614-1629-6

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