Authors:
Nizar Sallem
1
;
Michel Devy
1
;
Radu Rusu
2
and
Suat Gedikili
3
Affiliations:
1
Université de Toulouse, France
;
2
Open Perception, United States
;
3
Willow Garage, United States
Keyword(s):
Keypoints, Corner, Detection, RGB-D.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
Abstract:
Features detection is an important technique of image processing which aim is to find a subset, often discrete, of a query image satisfying uniqueness and discrimination criteria so that an image can be abstracted to the computed features. Detected features are then used in video indexing, registration, object and scene reconstruction, structure from motion, etc. In this article we discuss the definition and implementation of such features in the RGB-Depth space RGB-D.We focus on the corners as they are the most used features in image processing. We show the advantage of using 3D data over image only techniques and the power of combining geometric and colorimetric information to find corners in a scene.