Generic Object Recognition

Hegazy, Doaa; Denzler, Joachim

doi:10.4230/DagSemProc.08422.8

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Generic Object Recognition

Authors Doaa Hegazy, Joachim Denzler

Part of: Volume: Dagstuhl Seminar Proceedings, Volume 8422
Part of: Series: Dagstuhl Seminar Proceedings (DagSemProc)
License: Creative Commons Attribution 4.0 International license
Publication Date: 2009-01-29

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DOI: 10.4230/DagSemProc.08422.8
URN: urn:nbn:de:0030-drops-18668

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Generic object recognition
Boosting
Range images

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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.

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Doaa Hegazy and Joachim Denzler. Generic Object Recognition. In Computer Vision in Camera Networks for Analyzing Complex Dynamic Natural Scenes. Dagstuhl Seminar Proceedings, Volume 8422, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009) https://doi.org/10.4230/DagSemProc.08422.8

Author Details

Doaa Hegazy

Joachim Denzler

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