Towards automatically learning an implicit model from 2D-images based on a local similarity analysis of contours

Author

Pechtel, D. ; Kuhnert, K.-D.

Author_Institution

Inst. for Realtime Data Process., Siegen Univ., Germany

Volume

1

fYear

2000

fDate

2000

Firstpage

590

Abstract

The article deals with enabling an intelligent system to autonomously learn an implicit model of its environment. An unsupervised learning method is presented which learns the topological connections of different object views. Moreover, the method is able to distinguish between different objects. Based on a systematic local analysis of the objects´ contours, the method unites learning a topology (i.e. navigation) and object recognition into one framework

Keywords

image matching; image recognition; intelligent control; mobile robots; object recognition; path planning; robot vision; topology; unsupervised learning; 2D images; automatic learning; autonomous learning; contour analysis; environment model; implicit model; intelligent mobile robots; intelligent system; local similarity analysis; navigation learning; object recognition; object views; systematic local analysis; topological connections; topology learning; unsupervised learning; Data processing; Ear; Image sequences; Intelligent robots; Learning systems; Navigation; Organisms; Robot vision systems; Solid modeling; Topology;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Robots and Systems, 2000. (IROS 2000). Proceedings. 2000 IEEE/RSJ International Conference on

Conference_Location

Takamatsu

Print_ISBN

0-7803-6348-5

Type

conf

DOI

10.1109/IROS.2000.894668

Filename

894668