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 :
بازگشت