On Matching Algorithms for the Recognition of Objects in Cluttered Background

Authors:
Josef Kittler;Alireza Ahmadyfard
Affiliations:
-;-
Venue:
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Year:
2001

Citing 4
Cited 0

Recognizing solid objects by alignment with an image

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Structural Matching in Computer Vision Using Probabilistic Relaxation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Object Recognition by Geometric Hashing

ECCV '90 Proceedings of the First European Conference on Computer Vision
Object Recognition by Alignment Using Invariant Projections of Planar Surfaces

Object Recognition by Alignment Using Invariant Projections of Planar Surfaces

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Abstract

An experimental comparative study of three matching methods for the recognition of 3D objects from a 2D view is carried out. The methods include graph matching, geometric hashing and the alignment technique. The same source of information is made available to each method to ensure that the comparison is meaningful. The experiments are designed to measure the performance of the methods in different imaging conditions. We show that matching by geometric hashing and alignment is very sensitive to clutter and measurement errors. Thus in realistic scenarios graph matching is superior to the other methods in terms of both recognition accuracy and computational complexity.