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International Conference on Intelligent Computing

ICIC 2015: Intelligent Computing Theories and Methodologies pp 378–387Cite as

Pedestrian Detection and Counting Based on Ellipse Fitting and Object Motion Continuity for Video Data Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9225))

Abstract

In order to detect and count pedestrians in different kinds of scenes, this paper put forward a method of solving the problem on video sequences captured from a fixed camera. After preprocessing operations on the original video sequences (Gaussian mixture modeling, three-frame-differencing, image binaryzation, Gaussian filtering, dilation and erosion) we extract the relatively complete pedestrian contours. Then we use the least square ellipse fitting method on those contours that has been extracted, the center of the ellipse is undoubtedly regarded as the tracking point of a pedestrian. With those points, a pedestrian matching pursuit and counting algorithm based on object motion continuity is used for tracking and counting pedestrians, this method can be better used in those scenes which are sparse and rarely obscured. Experiments validate that our pedestrian matching pursuit and counting algorithm has obvious superiorities: good real-time performance and high accuracy.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (No. 61373109, No. 61003127), State Key Laboratory of Software Engineering (SKLSE2012-09-31).

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Authors and Affiliations

  1. College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China

    Yaning Wang & Hong Zhang

  2. Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System, Wuhan, China

    Yaning Wang & Hong Zhang

Authors
  1. Yaning Wang
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  2. Hong Zhang
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Corresponding author

Correspondence to Hong Zhang .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytecnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

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© 2015 Springer International Publishing Switzerland

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Wang, Y., Zhang, H. (2015). Pedestrian Detection and Counting Based on Ellipse Fitting and Object Motion Continuity for Video Data Analysis. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9225. Springer, Cham. https://doi.org/10.1007/978-3-319-22180-9_37

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  • DOI: https://doi.org/10.1007/978-3-319-22180-9_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22179-3

  • Online ISBN: 978-3-319-22180-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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