Skip to Main content Skip to Navigation
New interface
Journal articles

Matching and Clustering: Two Steps Towards Object Modelling in Computer Vision

Patrick Gros 1, 2 
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : In this article, we present a general frame for a system of au tomatic modeling and recognition of 3D polyhedral objects. Such a system has many applications for robotics: e.g., recog nition, localization, and grasping. Here we focus on one main aspect of the system: when many images of one 3D object are taken from different unknown viewpoints, how to recognize those that represent the same aspect of the object? Briefly, is it possible to determine automatically if two images are similar or not? The two stages detailed in the article are the matching of two images and the clustering of a set of images. Matching consists of finding the common features of two images while no information is known about the image contents, the motion, or the calibration of the camera. Clustering consists of regrouping into sets the images representing a same aspect of the modeled objects. For both stages, experimental results on real images are shown.
Document type :
Journal articles
Complete list of metadata

Cited literature [22 references]  Display  Hide  Download
Contributor : Perception team Connect in order to contact the contributor
Submitted on : Wednesday, May 4, 2011 - 5:01:33 PM
Last modification on : Friday, February 4, 2022 - 3:34:01 AM
Long-term archiving on: : Friday, August 5, 2011 - 2:26:30 AM

Files produced by the author(s)




Patrick Gros. Matching and Clustering: Two Steps Towards Object Modelling in Computer Vision. The International Journal of Robotics Research, 1995, 14 (6), pp.633--642. ⟨10.1177/027836499501400608⟩. ⟨inria-00590038⟩



Record views


Files downloads