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Low Frequency Response and Random Feature Selection Applied to Face Recognition

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Image Analysis and Recognition (ICIAR 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4633))

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Abstract

A novel method for face recognition based on some biological aspects of infant vision is proposed in this paper. The biological hypotheses of this method are based on the role of the response to low frequencies at early stages, and some conjectures concerning how an infant detects subtle features (stimulating points) from a face. In order to recognize a face from different images of it we make use of a bank of dynamic associative memories (DAM). As the infant vision responds to low frequencies of the signal, a low-filter is first used to remove high frequency components from the image. We then detect subtle features in the image by means of a random feature selection detector. At last, the network of DAMs is fed with this information for training and recognition. To test the accuracy of the proposal a benchmark of faces is used.

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Mohamed Kamel Aurélio Campilho

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© 2007 Springer-Verlag Berlin Heidelberg

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Vázquez, R.A., Sossa, H., Garro, B.A. (2007). Low Frequency Response and Random Feature Selection Applied to Face Recognition. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_73

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  • DOI: https://doi.org/10.1007/978-3-540-74260-9_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74258-6

  • Online ISBN: 978-3-540-74260-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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