A scale invariant local image descriptor for visual homing

Authors:
Andrew Vardy;Franz Oppacher
Affiliations:
School of Computer Science, Carleton University, Ottawa, Canada;School of Computer Science, Carleton University, Ottawa, Canada
Venue:
Biomimetic Neural Learning for Intelligent Robots
Year:
2005

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Abstract

A descriptor is presented for characterizing local image patches in a scale invariant manner. The descriptor is biologically-plausible in that the necessary computations are simple and local. Two different methods for robot visual homing based on this descriptor are also presented and tested. The first method utilizes the common technique of corresponding descriptors between images. The second method determines a home vector more directly by finding the stationary local image patch most similar between the two images. We find that the first method exceeds the performance of Franz et. al's warping method. No statistically significant difference was found between the second method and the warping method.