A SELF-ORGANIZING MULTIPLE-VIEW REPRESENTATION OF 3D OBJECTS

被引：106

作者：

EDELMAN, S ^{[1
]}

WEINSHALL, D ^{[1
]}

机构：

[1] MIT,DEPT BRAIN & COGNIT SCI,CTR BIOL INFORMAT PROC,CAMBRIDGE,MA 02139

来源：

BIOLOGICAL CYBERNETICS | 1991年 / 64卷 / 03期

关键词：

D O I：

10.1007/BF00201981

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We explore representation of 3D objects in which several distinct 2D views are stored for each object. We demonstrate the ability of a two-layer network of thresholded summation units to support such representations. Using unsupervised Hebbian relaxation, the network learned to recognize ten objects from different viewpoints. The training process led to the emergence of compact representations of the specific input views. When tested on novel views of the same objects, the network exhibited a substantial generalization capability. In simulated psychophysical experiments, the network's behavior was qualitatively similar to that of human subjects.

引用

页码：209 / 219

页数：11