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Object Motion Detection Methods for Real-Time Video Surveillance: A Survey with Empirical Evaluation

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Smart Systems and IoT: Innovations in Computing

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 141))

Abstract

Automated moving object detection and analysis assumes a great significance in video surveillance. This article presents a comprehensive survey on the techniques of object-in-motion detection for video surveillance. In this paper, eight methods of object detection in video streams are implemented and evaluated empirically on five quality parameters for identifying the efficiency and effectiveness of these methods. For objective assessments of these methods, a standard dataset “CDnet2012” is used which consists of six different rigorous scenarios. In conclusion, an attempt has been made to identify the best method for different scenarios, employable in real-time video surveillance.

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Author information

Authors and Affiliations

  1. SoCSE, UPES, Dehradun, Uttarakhand, India

    Surender Singh, Ajay Prasad & Kingshuk Srivastava

  2. IPR Management Services, TCS, Bhubneswar, Uttarakhand, India

    Suman Bhattacharya

Authors
  1. Surender Singh
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  2. Ajay Prasad
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  3. Kingshuk Srivastava
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  4. Suman Bhattacharya
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Corresponding author

Correspondence to Surender Singh .

Editor information

Editors and Affiliations

  1. College of Engineering, Iowa State University, Ames, IA, USA

    Arun K. Somani

  2. School of Computing and Information Technology, Manipal University Jaipur, Jaipur, Rajasthan, India

    Rajveer Singh Shekhawat

  3. Department of Information Technology, Manipal University Jaipur, Jaipur, Rajasthan, India

    Ankit Mundra

  4. Department of Information Technology, Manipal University Jaipur, Jaipur, Rajasthan, India

    Sumit Srivastava

  5. School of Computing and Information Technology, Manipal University Jaipur, Jaipur, Rajasthan, India

    Vivek Kumar Verma

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Singh, S., Prasad, A., Srivastava, K., Bhattacharya, S. (2020). Object Motion Detection Methods for Real-Time Video Surveillance: A Survey with Empirical Evaluation. In: Somani, A.K., Shekhawat, R.S., Mundra, A., Srivastava, S., Verma, V.K. (eds) Smart Systems and IoT: Innovations in Computing. Smart Innovation, Systems and Technologies, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-13-8406-6_63

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