On-line Object Segmentation through Human-Robot Interaction

Title
On-line Object Segmentation through Human-Robot Interaction
Authors
김수환김동환박성기
Keywords
Object Segmentation; Human-Robot Interaction; Gesture Recognition; Watershed Segmentation
Issue Date
2010-10
Publisher
The 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
Citation
, 1734-1739
Abstract
In this paper we propose a new method for on-line object segmentation through human-robot interaction. Particularly, we define three types of human gestures for object learning by the size of target objects; holding small objects, pointing at medium ones and contacting two corners of large ones. The regions of interest where objects are likely to be located are interpreted from those gestures and represented as rectangles in captured images. For object segmentation, we suggest a marker-based watershed segmentation method which segregates an object within a region of interest in real-time performance. Experimental results show that the segmentation quality of our method is as good as that of the GrabCut algorithm, but the computational time of ours is so much faster that it is appropriate for practical applications.
URI
http://pubs.kist.re.kr/handle/201004/39131
Appears in Collections:
KIST Publication > Conference Paper
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE