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A Survey on Human Group Activity Recognition by Analysing Person Action from Video Sequences Using Machine Learning Techniques

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Optimization in Machine Learning and Applications

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

There has been a tremendous advance in machine learning techniques especially for automatic group activity recognition (GAR) over the past few decades. This review article surveys the modern advancement made towards video-based group activity recognition technique. Various applications, including video surveillance systems, sports analytics and human behaviour for robotics characterization, require a group activity recognition system. Comprehensive reviews of machine learning (ML) techniques like hidden Markov models (HMMs), graphical method and support vector machines employed in GAR are being discussed. A comprehensive review on the latest progress in deep learning model has delivered important developments in GAR performance; those are also presented. The main purpose of this survey is to broadly categorize and analyse GAR according to handcrafted features based on machine learning model and learned features based on deep model. Various GAR models illustrated by considering activities of individual person, person-to-person interaction, person-to-group interaction and group interaction using temporal sequence information from video frames for recognition of group activity are discussed. The review facilitates in diverse applications, and the models described in different applications present specifically in surveillance, sport analytics, video summary, etc.

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Authors and Affiliations

  1. D.Y. Patil College of Engineering, Akurdi, Pune, India

    Smita Kulkarni

  2. Army Institute of Technology, Dighi, Pune, India

    Sangeeta Jadhav

  3. MIT Academy of Engineering, Alandi (D), Pune, India

    Smita Kulkarni & Debashis Adhikari

Authors
  1. Smita Kulkarni
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  2. Sangeeta Jadhav
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  3. Debashis Adhikari
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Corresponding author

Correspondence to Debashis Adhikari .

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Editors and Affiliations

  1. Department of Mechanical Engineering, Symbiosis Institute of Technology, Pune, Maharashtra, India

    Anand J. Kulkarni

  2. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

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Kulkarni, S., Jadhav, S., Adhikari, D. (2020). A Survey on Human Group Activity Recognition by Analysing Person Action from Video Sequences Using Machine Learning Techniques. In: Kulkarni, A., Satapathy, S. (eds) Optimization in Machine Learning and Applications. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0994-0_9

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