DocumentCode
2237932
Title
Distance metric between 3D models and 2D images for recognition and classification
Author
Weinshall, D. ; Basri, Ronen
Author_Institution
Inst. of Comput. Sci., Hebrew Univ. of Jerusalem, Israel
fYear
1993
fDate
15-17 Jun 1993
Firstpage
220
Lastpage
225
Abstract
A transformation metric to measure the similarity between 3-D models and 2-D images is proposed. The transformation metric measures the amount of affine deformation applied to the object to produce the given image. A simple, closed-form solution for this metric is presented. This solution is optimal in transformation space, and it is used to bound the image metric from both above and below. The transformation metric can be used in several different ways in recognition and classification tasks
Keywords
image recognition; 2D images; 3D models; affine deformation; classification; closed-form solution; distance metric; image metric bounds; recognition; transformation metric; Closed-form solution; Computer science; Current measurement; Euclidean distance; Extraterrestrial measurements; Image recognition; Laboratories; Neuroscience; Object recognition; Paper technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location
New York, NY
ISSN
1063-6919
Print_ISBN
0-8186-3880-X
Type
conf
DOI
10.1109/CVPR.1993.340986
Filename
340986
Link To Document