A 3D Head Model From Stereo Images by a Self-Organizing Neural Network

被引：0

作者：

Sajo, Levente ^{[1
]}

Hoffmann, Miklos ^{[2
]}

Fazekas, Attila ^{[1
]}

机构：

[1] Univ Debrecen, Fac Informat, POB 12, H-4010 Debrecen, Hungary

[2] Eszterhazy Karoly Coll, Inst Math & Informat, H-3300 Eger, Hungary

来源：

JOURNAL FOR GEOMETRY AND GRAPHICS | 2009年 / 13卷 / 02期

关键词：

3D face model; stereo images; neural network;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper a model based approach is presented for generating 3D face models from two stereo images. The proposed method works with a small number of feature points of the face. The automatically registrated point pairs are used to reconstruct their 3D correspondence, then a predefined general face model is adjusted to the reconstructed 3D points. Fitting the general face model to the feature points is made iteratively by applying a self-organizing neural network.

引用

页码：209 / 220

页数：12

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