Title :
Learning structural concept with 3-D information of objects
Author :
Dong, Gang ; Yamaguchi, Tomohiro ; Yachida, Masahiko
Author_Institution :
Fac. of Eng. Sci., Osaka Univ., Japan
fDate :
29 Nov-2 Dec 1994
Abstract :
A new approach is proposed which learns structural concepts using learning from example, by taking 3D information of objects obtained from stereo vision as input for the system. In order to solve the scale problem in the quantitative representation of 3D information, the concept description language (CDL) is defined which represents the 3D relations of surface pairs of objects qualitatively. This CDL representation also serves as the intermediate description between the quantitative values obtained from the vision process and the abstract symbolic description utilized in the machine learning process
Keywords :
computer vision; image representation; learning by example; object recognition; stereo image processing; 3D object information; 3D relations; abstract symbolic description; concept description language; learning from example; machine learning process; quantitative representation; quantitative values; scale problem; stereo vision; structural concept learning; surface pairs; Costs; Image databases; Image recognition; Machine learning; Machine learning algorithms; Object recognition; Solid modeling; Spatial databases; Stereo vision; Systems engineering and theory;
Conference_Titel :
Intelligent Information Systems,1994. Proceedings of the 1994 Second Australian and New Zealand Conference on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-7803-2404-8
DOI :
10.1109/ANZIIS.1994.396983
