NDLI: Object modeling for environment perception through human-robot interaction

Content Provider	IEEE Xplore Digital Library
Author	Soohwan Kim Dong Hwan Kim Sung-Kee Park
Copyright Year	2010
Description	Author affiliation: Cognitive Robotics Center, Korea Institute of Science and Technology, Seoul, Korea (Soohwan Kim; Dong Hwan Kim; Sung-Kee Park)
Abstract	In this paper we propose a new method of object modeling for environment perception through human-robot interaction. Particularly, within a multi-modal object modeling architecture, we tackle the gestural language part using a stereo camera. To do that, we define three human gestures based on the size of target objects; holding small objects, pointing at medium ones, and contacting two corner points of large ones. When a user indicates where the target object is located in the environment, the robot interprets the user's gesture and captures one or more images including the target objects. The region of interest where a target object is likely to be located in the captured image is estimated from the environmental context and the user's gesture. Finally, given an image with a region of interest, the robot performs foreground/background segmentation automatically. Here, we suggest a marker-based watershed segmentation method for object segmentation. 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 on-line interactive object modeling.
Starting Page	2328
Ending Page	2333
File Size	976432
Page Count	6
File Format	PDF
ISBN	9781424474530
e-ISBN	9788993215021
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-27
Publisher Place	Korea (South)
Access Restriction	Subscribed
Rights Holder	IEEE International Conference on Control & Automation
Subject Keyword	Image segmentation Histograms human-robot interaction Image color analysis object segmentation watershed segmentation Humans Object segmentation Robots Pixel Object modeling
Content Type	Text
Resource Type	Article

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