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Authors: Xin Wang ; Maja Rudinac and Pieter P. Jonker

Affiliation: Delft University of Technology, Netherlands

Keyword(s): Unknown Environment, Saliency Detection, Tracking, Online Object Segmentation, Mobile Robots, Convergent Vision System.

Related Ontology Subjects/Areas/Topics: Active and Robot Vision ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Motion, Tracking and Stereo Vision ; Segmentation and Grouping ; Visual Attention and Image Saliency

Abstract: In this paper we present a novel vision system for object-driven and online learning based segmentation of unknown objects in a scene. The main application of this system is for mobile robots exploring unknown environments, where unknown objects need to be inspected and segmented from multiple viewpoints. In an initial step, objects are detected using a bottom-up segmentation method based on salient information. The cluster with the most salient points is assumed to be the most dominant object in the scene and serves as an initial model for online segmentation. Then the dominant object is tracked by a Lucas-Kanade tracker and the object model is constantly updated and learned online based on Random Forests classifier. To refine the model a two-step object segmentation using Gaussian Mixture Models and graph cuts is applied. As a result, the detailed contour information of the dominant unknown object is obtained and can further be used for object grasping and recognition. We tested ou r system in very challenging conditions with multiple identical objects, severe occlusions, illumination changes and cluttered background and acquired very promising results. In comparison with other methods, our system works online and requires no input from users. (More)

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Paper citation in several formats:
Wang, X.; Rudinac, M. and P. Jonker, P. (2012). ROBUST ONLINE SEGMENTATION OF UNKNOWN OBJECTS FOR MOBILE ROBOTS. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP; ISBN 978-989-8565-03-7; ISSN 2184-4321, SciTePress, pages 365-374. DOI: 10.5220/0003866803650374

@conference{visapp12,
author={Xin Wang. and Maja Rudinac. and Pieter {P. Jonker}.},
title={ROBUST ONLINE SEGMENTATION OF UNKNOWN OBJECTS FOR MOBILE ROBOTS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP},
year={2012},
pages={365-374},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003866803650374},
isbn={978-989-8565-03-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP
TI - ROBUST ONLINE SEGMENTATION OF UNKNOWN OBJECTS FOR MOBILE ROBOTS
SN - 978-989-8565-03-7
IS - 2184-4321
AU - Wang, X.
AU - Rudinac, M.
AU - P. Jonker, P.
PY - 2012
SP - 365
EP - 374
DO - 10.5220/0003866803650374
PB - SciTePress