DocumentCode :
2300161
Title :
Assessing feature importance for verification and pose refinement
Author :
West, Geoff A W
Author_Institution :
Dept. of Comput. Sci., Curtin Univ. of Technol., Bentley, WA, Australia
Volume :
1
fYear :
1996
fDate :
25-29 Aug 1996
Firstpage :
30
Abstract :
Object recognition can be defined as consisting of two main stages: indexing and verification, Indexing has received much attention in the literature with many schemes developed. However verification has received less attention and is generally used in its simplest form. This paper discusses evaluation techniques for assessing features in the context of verification and pose refinement strategies. Two metrics are considered: a typical Euclidean metric and the Hausdorff metric which is attracting interest in the vision community. These techniques can be used for the design and integration of indexing and verification stages of object recognition
Keywords :
image recognition; object recognition; Euclidean metric; Hausdorff metric; feature importance assessment; indexing; object recognition; pose refinement; verification; Detectors; Error correction; Euclidean distance; Gaussian noise; Geometry; Image edge detection; Object recognition; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
ISSN :
1051-4651
Print_ISBN :
0-8186-7282-X
Type :
conf
DOI :
10.1109/ICPR.1996.545986
Filename :
545986
Link To Document :
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