DocumentCode
353352
Title
Mesh construction with fast soft vector quantisation
Author
Borghese, N. Alberto ; Ferrari, Stefano
Author_Institution
Lab. of Human Motion Anal. & Virtual Reality, CNR, Milano, Italy
Volume
5
fYear
2000
fDate
2000
Firstpage
473
Abstract
In this paper a method to accelerate soft vector quantisation (VQ), making it a quasi-real time procedure, is described. Through the local analysis of the data density a criterion to set a reasonable value of the parameters and to initialise the position of the reference vectors (hyper-box preprocessing), allows to cut about 75% of the iterations and to make the computational cost of each iteration constant, independent of the number of sampled points. Moreover, it makes soft VQ of possible implementation on parallel machines. Overall the processing time with hyper-box pre-processing can be brought down to 3%. This method, in conjunction with Delaunay tessellation, has been extensively applied to the construction of 3D triangular meshes from dense noisy data. Results on the reconstruction of 3D models of human faces are reported and discussed
Keywords
computational complexity; mesh generation; neural nets; noise; vector quantisation; 3D model reconstruction; 3D triangular meshes; Delaunay tessellation; computational cost; dense noisy data; fast soft vector quantisation; human faces; hyper-box preprocessing; mesh construction; neural nets; parallel implementation; quasi-real-time procedure; reference vector position initialisation; soft VQ; Acceleration; Annealing; Computational efficiency; Data analysis; Humans; Image reconstruction; Laboratories; Motion analysis; Vector quantization; Virtual reality;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location
Como
ISSN
1098-7576
Print_ISBN
0-7695-0619-4
Type
conf
DOI
10.1109/IJCNN.2000.861514
Filename
861514
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