Title :
Multiple objects recognition for industrial robot applications
Author :
Kyekyung Kim ; Sangseung Kang ; Jaehong Kim ; Jaeyeon Lee ; Joongbae Kim ; Jinho Kim
Author_Institution :
Dept. of Intell. Cognitive Technol., ETRI, Daejeon, South Korea
fDate :
Oct. 30 2013-Nov. 2 2013
Abstract :
Vision-based object recognition has been studied intensively because of many application fields, especially, manufacturing process in industrial robot application. But it has been challenged due to illumination effect, diverse material object, atypical shape object, etc. In this paper, multiple object recognition including complex shape object has been proposed. The object is consisted of variable characteristic, which has reflection material surface wrapped by plastic or flexible shape. Object segmentation using back light and pose estimation by maximal axis detection, and object recognition by NN have developed. We have evaluated recognition performance on database of ETRI, which has acquired under various lighting conditions.
Keywords :
image segmentation; industrial robots; neural nets; object recognition; pose estimation; ETRI; NN; back light; complex shape object; diverse material object; flexible shape; illumination effect; industrial robot applications; lighting conditions; manufacturing process; maximal axis detection; multiple object recognition; multiple objects recognition; object segmentation; plastic; pose estimation; reflection material surface; vision-based object recognition; Edge detection; Object recognition; Object segmentation; Pose estimation;
Conference_Titel :
Ubiquitous Robots and Ambient Intelligence (URAI), 2013 10th International Conference on
Conference_Location :
Jeju
Print_ISBN :
978-1-4799-1195-0
DOI :
10.1109/URAI.2013.6677361