Geometric fusion for a hand-held 3D sensor
Author(s) -
Adrian Hilton,
J. Illingworth
Publication year - 2000
Publication title -
machine vision and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 68
eISSN - 1432-1769
pISSN - 0932-8092
DOI - 10.1007/s001380050123
Subject(s) - computer vision , sensor fusion , geometric modeling , computer science , transformation (genetics) , artificial intelligence , geometric transformation , geometric shape , range (aeronautics) , fusion , surface (topology) , geometric data analysis , representation (politics) , geometric primitive , volume (thermodynamics) , surface reconstruction , image (mathematics) , mathematics , engineering , geometry , philosophy , law , aerospace engineering , linguistics , chemistry , biochemistry , quantum mechanics , political science , physics , politics , gene
. This article presents a geometric fusion algorithm developed for the reconstruction of 3D surface models from hand-held sensor data. Hand-held systems allow full 3D movement of the sensor to capture the shape of complex objects. Techniques previously developed for reconstruction from conventional 2.5D range image data cannot be applied to hand-held sensor data. A geometric fusion algorithm is introduced to integrate the measured 3D points from a hand-held sensor into a single continuous surface. The new geometric fusion algorithm is based on the normal-volume representation of a triangle, which enables incremental transformation of an arbitrary mesh into an implicit volumetric field function. This system is demonstrated for reconstruction of surface models from both hand-held sensor data and conventional 2.5D range images.
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