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Learning Visual Dictionaries from Class-Specific Superpixel Segmentation

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Computer Analysis of Images and Patterns (CAIP 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11678))

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Abstract

Visual dictionaries (Bag of Visual Words - BoVW) can be a very powerful technique for image description whenever exists a reduced number of training images, being an attractive alternative to deep learning techniques. Nevertheless, models for BoVW learning are usually unsupervised and rely on the same set of visual words for all images in the training set. We present a method that works with small supervised training sets. It first generates superpixels from multiple images of a same class, for interest point detection, and then builds one visual dictionary per class. We show that the detected interest points can be more relevant than the traditional ones (e.g., grid sampling) in the context of a given application—the classification of intestinal parasite images. The study uses three image datasets, with a total of 15 different species of parasites, and a diverse class, namely impurity, which makes the problem difficult with examples similar to all the remaining classes of parasites.

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Acknowledgments

The authors thank FAPESP (grants 2014/12236-1 and 2017/03940-5) and CNPq (grant 303808/2018-7) for the financial support.

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Authors and Affiliations

  1. Laboratory of Image Data Science, Institute of Computing, University of Campinas, Campinas, SP, Brazil

    César Castelo-Fernández & Alexandre X. Falcão

Authors
  1. César Castelo-Fernández
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  2. Alexandre X. Falcão
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Corresponding author

Correspondence to César Castelo-Fernández .

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Editors and Affiliations

  1. Department of Computer and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano (SA), Italy

    Mario Vento

  2. Department of Computer and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano (SA), Italy

    Gennaro Percannella

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Castelo-Fernández, C., Falcão, A.X. (2019). Learning Visual Dictionaries from Class-Specific Superpixel Segmentation. In: Vento, M., Percannella, G. (eds) Computer Analysis of Images and Patterns. CAIP 2019. Lecture Notes in Computer Science(), vol 11678. Springer, Cham. https://doi.org/10.1007/978-3-030-29888-3_14

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  • DOI: https://doi.org/10.1007/978-3-030-29888-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29887-6

  • Online ISBN: 978-3-030-29888-3

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