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International Conference on Image Processing and Communications

IP&C 2016: Image Processing and Communications Challenges 8 pp 179–186Cite as

Action Recognition Using Silhouette Sequences and Shape Descriptors

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 525))

Abstract

The paper provides an approach for human action recognition based on shape analysis. The developed approach is intended for specific type of data, namely sequences of binary silhouettes representing a person performing an action, and consists of several processing steps including shape description as well as similarity or dissimilarity estimation. The approach can deal with sequences of different length without removing any frames. The paper also provides some experimental results showing the classification accuracy and overall recognition effectiveness of the proposed approach using several popular shape description algorithms, namely the Two-Dimensional Fourier Descriptor, Generic Fourier Descriptor, Point Distance Histogram and UNL-Fourier Descriptor.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Żołnierska 52, 71-210, Szczecin, Poland

    Katarzyna Gościewska & Dariusz Frejlichowski

Authors
  1. Katarzyna Gościewska
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  2. Dariusz Frejlichowski
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Corresponding author

Correspondence to Dariusz Frejlichowski .

Editor information

Editors and Affiliations

  1. Institute of Telecommunications and Computer Sciences, UTP University of Science and Technology, Bydgoszcz, Poland

    Ryszard S. Choraś

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Gościewska, K., Frejlichowski, D. (2017). Action Recognition Using Silhouette Sequences and Shape Descriptors. In: Choraś, R. (eds) Image Processing and Communications Challenges 8. IP&C 2016. Advances in Intelligent Systems and Computing, vol 525. Springer, Cham. https://doi.org/10.1007/978-3-319-47274-4_21

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  • DOI: https://doi.org/10.1007/978-3-319-47274-4_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47273-7

  • Online ISBN: 978-3-319-47274-4

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