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An Efficient Approach to Feature Extraction for Crowd Density Estimation

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Computing, Communication and Signal Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 810))

Abstract

Crowd feature extraction is important step for crowd density estimation. This paper proposes a simple and novel approach of feature extraction applicable for crowd density estimation. A 5 × 5 mask is proposed for extraction of density, which finds isolated components in the image. This helps in classification of the density in five levels using SVM and ANN classifiers. The method can be used for intelligent surveillance system in public places. It can easily be used for embedded applications.

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References

  1. Loy, C.C., Chen, K., Gong, S., Xiang, T.: Crowd Counting and Profiling: Methodology and Evaluation (2013)

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  2. Saleh, S.A.M., Suandi, S.A., Ibrahim, H.: Recent survey on crowd density estimation and counting for visual surveillance, pp. 103–114. Elsevier Ltd. (2015)

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Book Chapter

  1. Nemade, N.A., Gohokar, V.V.: Crowd Density as Dynamic Texture: Behavior Estimation and Classification, Information and Communication Technology, AISC, vol. 625, www.springer.com/us/book/9789811055072 (2016)

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Author information

Authors and Affiliations

  1. Electronics & Telecommunication Engineering Department, SSGM College of Engineering, Shegaon, India

    Neeta Anil Nemade

  2. Electronics & Telecommunication Engineering Department, Maharashtra Institute of Technology, Kothrud, Pune, India

    V. V. Gohokar

Authors
  1. Neeta Anil Nemade
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  2. V. V. Gohokar
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Corresponding author

Correspondence to Neeta Anil Nemade .

Editor information

Editors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, Maharashtra, India

    Brijesh Iyer

  2. Department of Electronics and Telecommunication Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, Maharashtra, India

    S.L. Nalbalwar

  3. Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Nagendra Prasad Pathak

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© 2019 Springer Nature Singapore Pte Ltd.

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Nemade, N.A., Gohokar, V.V. (2019). An Efficient Approach to Feature Extraction for Crowd Density Estimation. In: Iyer, B., Nalbalwar, S., Pathak, N. (eds) Computing, Communication and Signal Processing . Advances in Intelligent Systems and Computing, vol 810. Springer, Singapore. https://doi.org/10.1007/978-981-13-1513-8_36

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  • DOI: https://doi.org/10.1007/978-981-13-1513-8_36

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1512-1

  • Online ISBN: 978-981-13-1513-8

  • eBook Packages: EngineeringEngineering (R0)

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