ICDSMLA 2019 pp 356-364 | Cite as

Human Activity Recognition on Multivariate Time Series Data: A Technical Review

  • I. Anitha Rani
  • A. VadivelEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 601)


Recognizing human activities from video sequences or sensor data is a challenging task in computer vision. Background clutter, partial occlusion, changes in viewpoint, lighting, and appearance are creating bottlenecks in the recognition of activity. In this paper, we provide a comprehensive review by categorizing the activity recognition approaches that have been applied on multivariate time series data. The review provides insights of each method, research issues and performance issue.


Human action recognition Feature extraction Human pose Spatio-temporal features Real time video surveillance 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSRM UniversityAmaravathiIndia

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