A fast algorithm for ICP-based 3D shape biometrics

In a biometrics scenario, gallery images are enrolled into the database ahead of the matching step, which gives us the opportunity to build related data structures before the probe shape is examined. In this paper, we present a novel approach, called “Pre-computed Voxel Nearest Neighbor”, to reduce...

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Bibliographic Details
Published inComputer vision and image understanding Vol. 107; no. 3; pp. 195 - 202
Main Authors Yan, Ping, Bowyer, Kevin W.
Format Journal Article
LanguageEnglish
Published San Diego, CA Elsevier Inc 01.09.2007
Elsevier
Subjects
3D shape
Applied sciences
Artificial intelligence
Biometrics
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Iterative closest point
Pattern recognition. Digital image processing. Computational geometry
Shape matching
Software
Biometrics
Iterative closest point
3D shape
Shape matching
Nearest neighbour
Computer vision
Face recognition
Image processing
Iterative method
Object recognition
Voxel
Facies
Ear
Database
Tridimensional image
Fast algorithm
Data structure
Pattern matching
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Summary:In a biometrics scenario, gallery images are enrolled into the database ahead of the matching step, which gives us the opportunity to build related data structures before the probe shape is examined. In this paper, we present a novel approach, called “Pre-computed Voxel Nearest Neighbor”, to reduce the computational time for shape matching in a biometrics context. The approach shifts the heavy computation burden to the enrollment stage, which is done offline. Experiments in 3D ear biometrics with 369 subjects and 3D face biometrics with 219 subjects demonstrate the effectiveness of our approach.
ISSN:1077-3142
1090-235X
DOI:10.1016/j.cviu.2006.11.001