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Half Profile Face Image Clustering Based on Feature Points

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Image Processing and Communications Challenges 10 (IP&C 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 892))

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Abstract

In this paper the problem of hierarchical half profile face image clustering is considered. In order to solve this problem the computer vision methods based on a different local feature detectors like: Harris, BRISK, SURF, SIFT and FSIFT have been examined. For image clustering task the agglomerative hierarchical clustering procedure based on a dissimilarity matrix have been used. The achieved results have been compared to each other.

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Author information

Authors and Affiliations

  1. Institute of Control and Industrial Electronics, Warsaw University of Technology, Warsaw, Poland

    Grzegorz Sarwas & Sławomir Skoneczny

Authors
  1. Grzegorz Sarwas
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  2. Sławomir Skoneczny
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Corresponding author

Correspondence to Grzegorz Sarwas .

Editor information

Editors and Affiliations

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

    Michał Choraś

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

    Ryszard S. Choraś

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Sarwas, G., Skoneczny, S. (2019). Half Profile Face Image Clustering Based on Feature Points. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications Challenges 10. IP&C 2018. Advances in Intelligent Systems and Computing, vol 892. Springer, Cham. https://doi.org/10.1007/978-3-030-03658-4_17

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