Title
3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints
Abstract
This article introduces a novel representation for three-dimensional (3D) objects in terms of local affine-invariant descriptors of their images and the spatial relationships between the corresponding surface patches. Geometric constraints associated with different views of the same patches under affine projection are combined with a normalized representation of their appearance to guide matching and reconstruction, allowing the acquisition of true 3D affine and Euclidean models from multiple unregistered images, as well as their recognition in photographs taken from arbitrary viewpoints. The proposed approach does not require a separate segmentation stage, and it is applicable to highly cluttered scenes. Modeling and recognition results are presented.
Year
DOI
Venue
2006
10.1007/s11263-005-3674-1
International Journal of Computer Vision
Keywords
Field
DocType
three-dimensional object recognition,image-based modeling,affine-invariant image descriptors,multi-view geometry
Affine transformation,Affine shape adaptation,Computer vision,Harris affine region detector,Normalization (statistics),3D single-object recognition,Pattern recognition,Computer science,Segmentation,Object model,Artificial intelligence,Euclidean geometry
Journal
Volume
Issue
ISSN
66
3
0920-5691
Citations 
PageRank 
References 
204
15.33
47
Authors
4
Search Limit
100204
Name
Order
Citations
PageRank
Fred Rothganger126219.17
Svetlana Lazebnik27379449.66
Cordelia Schmid3285811983.22
Jean Ponce412182902.31