Title
3D scene retrieval and recognition with Depth Gradient Images
Abstract
The intention of the strategy proposed in this paper is to solve the object retrieval problem in highly complex scenes using 3D information. In the worst case scenario the complexity of the scene includes several objects with irregular or free-form shapes, viewed from any direction, which are self-occluded or partially occluded by other objects with which they are in contact and whose appearance is uniform in intensity/color. This paper introduces and analyzes a new 3D recognition/pose strategy based on DGI (Depth Gradient Images) models. After comparing it with current representative techniques, we can affirm that DGI has very interesting prospects.The DGI representation synthesizes both surface and contour information, thus avoiding restrictions concerning the layout and visibility of the objects in the scene. This paper first explains the key concepts of the DGI representation and shows the main properties of this method in comparison to a set of known techniques. The performance of this strategy in real scenes is then reported. Details are also presented of a wide set of experimental tests, including results under occlusion, performance with injected noise and experiments with cluttered scenes of a high level of complexity.
Year
DOI
Venue
2011
10.1016/j.patrec.2011.03.016
Pattern Recognition Letters
Keywords
Field
DocType
current representative technique,free-form shape,depth gradient images,3d object representation models,scene retrieval,range image processing,wide set,cluttered scene,experimental test,complex scene,real scene,3d recognition and pose,3d computer vision,object retrieval,dgi representation,contour information
Computer vision,Visibility,Pattern recognition,Computer science,Artificial intelligence,Worst-case scenario
Journal
Volume
Issue
ISSN
32
9
Pattern Recognition Letters
Citations 
PageRank 
References 
8
0.45
30
Authors
3
Name
Order
Citations
PageRank
Antonio Adán112422.27
Pilar Merchán26311.05
Santiago Salamanca36311.24