DocumentCode :
507922
Title :
On Object Perception in Enhanced Reality Environment for Robot Telecontrol
Author :
Wang, Chensheng ; Wang, Fei ; Wiegres, Tjamme
Author_Institution :
Sch. of Autom., Beijing Univ. of Posts & Telecommun., Beijing, China
Volume :
5
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
52
Lastpage :
56
Abstract :
Object recognition is one of the hot topics in computer vision. Existing techniques for object recognition are based on image processing, which tends to be incapable to recover the topological information of the object. In this paper, based on the analysis of human perceptual habit, a novel strategy for object recognition is proposed. The method perceives an object in the scene by means of existing shape knowledge coupling. And a mechanism is designed to grow the system intelligence by depositing the shape knowledge into a repository once a new object is encountered. This makes the system be in a constant way to become more and more intelligent. In addition, the proposed strategy is advantageous in rebuilding the whole object information with the support of the repository. Experiment results carried out in the enhanced reality environment for robot telecontrol shows that the proposed strategy is both valid and effective for the designed application.
Keywords :
computer vision; object recognition; telerobotics; visual perception; computer vision; enhanced reality environment; human perceptual habit; image processing; object perception; object recognition; robot telecontrol; Computer vision; Design automation; Electronic mail; Humans; Image reconstruction; Object recognition; Robot vision systems; Robotics and automation; Shape; Telecommunication computing; enhanced reality; object perception; object recognition; object reconstruction; robot telecontrol;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.13
Filename :
5363983
Link To Document :
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