Elastic graph matching on gabor feature representation at low image resolution

Authors:
Yasuomi D. Sato;Yasutaka Kuriya
Affiliations:
Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Wakamatsu, Kitakyushu, Japan,Frankfurt Institute for Advanced Studies (FIAS), Goethe University Frankfurt, ...;Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Wakamatsu, Kitakyushu, Japan
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Year:
2012

Citing 3
Cited 0

Distortion Invariant Object Recognition in the Dynamic Link Architecture

IEEE Transactions on Computers
Robust Real-Time Face Detection

International Journal of Computer Vision
Complex wavelet transform-based face recognition

EURASIP Journal on Advances in Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We progressively improve conventional elastic graph matching (EGM) algorithm. In the conventional EGM, each node of a model graph can difficultly detect its corresponding precise position for the most similar Gabor feature extraction on an input low-resolution image. Solving this problem and then finding such a position, we propose a method that the node is allowed to fit among pixels by interpolating aliased Gabor feature representation between the pixels, which is calculated with the others extracted at the neighbor pixels. The model graph can thereby move to the most likely and more precise positions on the input low-resolution image.