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ACCV
2006
Springer

Biologically Motivated Perceptual Feature: Generalized Robust Invariant Feature

9 years 4 months ago
Biologically Motivated Perceptual Feature: Generalized Robust Invariant Feature
Abstract. In this paper, we present a new, biologically inspired perceptual feature to solve the selectivity and invariance issue in object recognition. Based on the recent findings in neuronal and cognitive mechanisms in human visual systems, we develop a computationally efficient model. An effective form of a visual part detector combines a radial symmetry detector with a corner-like structure detector. A general context descriptor encodes edge orientation, edge density, and hue information using a localized receptive field histogram. We compare the proposed perceptual feature (G-RIF: generalized robust invariant feature) with the state-ofthe-art feature, SIFT, for feature-based object recognition. The experimental results validate the robustness of the proposed perceptual feature in object recognition.
Sungho Kim, In-So Kweon
Added 13 Jun 2010
Updated 13 Jun 2010
Type Conference
Year 2006
Where ACCV
Authors Sungho Kim, In-So Kweon
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