On-line Object Segmentation through Human-Robot Interaction
- On-line Object Segmentation through Human-Robot Interaction
- 김수환; 김동환; 박성기
- Object Segmentation; Human-Robot Interaction; Gesture Recognition; Watershed Segmentation
- Issue Date
- The 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
- , 1734-1739
- 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.
- Appears in Collections:
- KIST Publication > Conference Paper
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