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Cognitive Computation
Erschienen in: Cognitive Computation 4/2013

01.12.2013

A Perceptual Visual Feature Extraction Method Achieved by Imitating V1 and V4 of the Human Visual System

verfasst von: Sungho Kim, Soon Kwon, In So Kweon

Erschienen in: Cognitive Computation | Ausgabe 4/2013

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Abstract

In this paper, we present a new shape encoding method for object recognition. We first introduce a neuro-physiologically inspired visual part detector and shape encoder. The optimal form of the visual part detector is a combination of a circular symmetry detector and a corner-like structure detector. A perceptually novel shape descriptor, known as the curvature-orientation descriptor, is then discussed. This descriptor encodes the curvature as well as the dominant orientation. The perceptual shape encoder enhances the performance of feature matching and object recognition taken from standard test images. The results from the repeatability and object recognition tests validate the feasibility of the proposed perceptual feature extraction method.
Vorheriger Artikel Binocular Energy Estimation Based on Properties of the Human Visual System
Nächster Artikel Erratum to: Blame the Opponent! Effects of Multimodal Discrediting Moves in Public Debates

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Metadaten
Titel
A Perceptual Visual Feature Extraction Method Achieved by Imitating V1 and V4 of the Human Visual System
verfasst von
Sungho Kim
Soon Kwon
In So Kweon
Publikationsdatum
01.12.2013
Verlag
Springer US
Erschienen in
Cognitive Computation / Ausgabe 4/2013
Print ISSN: 1866-9956
Elektronische ISSN: 1866-9964
DOI
https://doi.org/10.1007/s12559-012-9194-8

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