Title: Histograms of Oriented Gradients for 3D Object Retrieval
Authors: Scherer, Maximilian
Walter, Michael
Schreck, Tobias
Citation: WSCG 2010: Full Papers Proceedings: 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS, p. 41-48.
Issue Date: 2010
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: http://wscg.zcu.cz/WSCG2010/Papers_2010/!_2010_FULL-proceedings.pdf
ISBN: 978-80-86943-88-6
Keywords: vyhledávání 3D objektů;3D modely;histogram
Keywords in different language: 3D object retrieval;3D models;histogram
Abstract: 3D object retrieval has received much research attention during the last years. To automatically determine the similarity between 3D objects, the global descriptor approach is very popular, and many competing methods for extracting global descriptors have been proposed to date. However, no single descriptor has yet shown to outperform all other descriptors on all retrieval benchmarks or benchmark classes. Instead, combinations of different descriptors usually yield improved performance over any single method. Therefore, enhancing the set of candidate descriptors is an important prerequisite for implementing effective 3D object retrieval systems. Inspired by promising recent results from image processing, in this paper we adapt the Histogram of Oriented Gradients (HOG) 2D image descriptor to the 3D domain. We introduce a concept for transferring the HOG descriptor extraction algorithm from 2D to 3D. We provide an implementation framework for extracting 3D HOG features from 3D mesh models, and present a systematic experimental evaluation of the retrieval effectiveness of this novel 3D descriptor. The results show that our 3D HOG implementation provides competitive retrieval performance, and is able to boost the performance of one of the best existing 3D object descriptors when used in a combined descriptor.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG 2010: Full Papers Proceedings

Files in This Item:
File Description SizeFormat 
Scherer.pdfPlný text588,8 kBAdobe PDFView/Open

Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/10871

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.