DITEC: Experimental analysis of an image characterization method based on the trace transform

Authors: Igor G. Olaizola, Iñigo Barandiaran, Basilio Sierra, Manuel Graña

Date: 21.02.2013


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Abstract

Global and local image feature extraction is one of the most common tasks in computer vision since they provide the basic information for further processes, and can be employed on several applications such as image search & retrieval, object recognition, 3D reconstruction, augmented reality, etc. The main parameters to evaluate a feature extraction algorithm are its discriminant capability, robustness and invariance behavior to certain transformations. However, other aspects such as computational performance or provided feature length can be crucial for domain specific applications with specific constraints (real-time, massive datasets, etc.). In this paper, we analyze the main characteristics of the DITEC method used both as global and local descriptor method. Our results show that DITEC can be effectively applied in both contexts.

BIB_text

@Article {
author = {Igor G. Olaizola, Iñigo Barandiaran, Basilio Sierra, Manuel Graña},
title = {DITEC: Experimental analysis of an image characterization method based on the trace transform},
volume = {1},
keywds = {

Feature Descriptor, Trace Transform, Image Matching, Image Characterization


}
abstract = {

Global and local image feature extraction is one of the most common tasks in computer vision since they provide the basic information for further processes, and can be employed on several applications such as image search & retrieval, object recognition, 3D reconstruction, augmented reality, etc. The main parameters to evaluate a feature extraction algorithm are its discriminant capability, robustness and invariance behavior to certain transformations. However, other aspects such as computational performance or provided feature length can be crucial for domain specific applications with specific constraints (real-time, massive datasets, etc.). In this paper, we analyze the main characteristics of the DITEC method used both as global and local descriptor method. Our results show that DITEC can be effectively applied in both contexts.


}
isi = {1},
date = {2013-02-21},
year = {2013},
}
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