NDLI: Online learning for automatic segmentation of 3D data

Content Provider	IEEE Xplore Digital Library
Author	Tombari, F. Di Stefano, L. Giardino, S.
Copyright Year	2011
Description	Author affiliation: DEIS, University of Bologna, Italy (Tombari, F.; Di Stefano, L.; Giardino, S.)
Abstract	We propose a method to perform automatic segmentation of 3D scenes based on a standard classifier, whose learning model is continuously improved by means of new samples, and a grouping stage, that enforces local consistency among classified labels. The new samples are automatically delivered to the system by a feedback loop based on a feature selection approach that exploits the outcome of the grouping stage. By experimental results on several datasets we demonstrate that the proposed online learning paradigm is effective in increasing the accuracy of the whole 3D segmentation thanks to the improvement of the learning model of the classifier by means of newly acquired, unsupervised data.
Starting Page	4857
Ending Page	4864
File Size	1038207
Page Count	8
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6094649
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three dimensional displays Training Feature extraction Support vector machines Shape Image color analysis Solid modeling
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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