English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/30346
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:


Unidimensional multiscale local features for object detection under rotation and mild occlusions

AuthorsVillamizar, Michael ; Sanfeliu, Alberto ; Andrade-Cetto, Juan
KeywordsComputer vision
Issue Date2007
CitationPattern Recognition and Image Analysis: 645-651 (2007)
AbstractIn this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows small changes in the histogram signature, giving robustness to partial occlusions. Local features over the object histogram are extracted during a Boosting learning phase, selecting the most discriminant features within a training histogram image set. The Integral Histogram has been used to compute local histograms in constant time.
DescriptionPresentado al 3rd Iberian Conference (IbPRIA-2007) celebrado en Girona (Spain) del 6 al 8 de junio.
Publisher version (URL)http://dx.doi.org/10.1007/978-3-540-72849-8_81
Appears in Collections:(IRII) Libros y partes de libros
Files in This Item:
File Description SizeFormat 
Unidimensional multiscale.pdf489,45 kBAdobe PDFThumbnail
Show full item record
Review this work

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.