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Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.08422.8
URN: urn:nbn:de:0030-drops-18668
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2009/1866/
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Hegazy, Doaa ;
Denzler, Joachim
Generic Object Recognition
Abstract
The object recognition problem has challenged the computer vision community for long time due to the huge change in the scale, occlusion and lighting conditions which have a great effect on the appearance of the objects. The problem of generic object recognition (GOR) has the previously mentioned difficulties in addition to the intra-class and inter-class variability problems. Despite the difficulties of the generic object recognition problem many approaches appeared trying to provide a solution to this problem. We present our model for 2D generic object recognition which achieves good performance on difficult object category datasets. Moreover, we present a model for generic 3D object recognition from range images.
BibTeX - Entry
@InProceedings{hegazy_et_al:DagSemProc.08422.8,
author = {Hegazy, Doaa and Denzler, Joachim},
title = {{Generic Object Recognition}},
booktitle = {Computer Vision in Camera Networks for Analyzing Complex Dynamic Natural Scenes},
series = {Dagstuhl Seminar Proceedings (DagSemProc)},
ISSN = {1862-4405},
year = {2009},
volume = {8422},
editor = {Joachim Denzler and Michael Koch},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2009/1866},
URN = {urn:nbn:de:0030-drops-18668},
doi = {10.4230/DagSemProc.08422.8},
annote = {Keywords: Generic object recognition, Boosting, Range images}
}
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Keywords: |
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Generic object recognition, Boosting, Range images |
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Collection: |
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08422 - Klausurtagung Lehrstuhl Joachim Denzler |
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Issue Date: |
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2009 |
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Date of publication: |
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29.01.2009 |
