Authors:
Manuel Grand-brochier
;
Christophe Tilmant
and
Michel Dhome
Affiliation:
Laboratoire des Sciences et Matriaux pour l’Electronique and et d’Automatique (LASMEA), France
Keyword(s):
Multi-scales analysis, Local descriptor, Robustness to image transformations, Elliptical-HOG.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Shape Analysis
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
This article proposes an approach to extraction (detection and description) of interest points based Fast-Hessian and E-HOG. SIFT and SURF are the two most used methods for this problem and their studies allow us to understand their construction and extract the various advantages (invariances, speeds, repeatability). Our goal is, firstly, to couple these advantages to create a new system (detector, descriptor and matching) and, secondly, to determine the characteristic points for different applications (image transformation, 3D reconstruction...). Our system must also be as invariant as possible for the image transformation (rotations, scales, viewpoints for example). Finally, we have to find a compromise between a good matching rate and the number of points matched. All the detector and descriptor parameters (orientations, thresholds, analysis shape) will be also detailed in this article.