English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/30367
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:


Enhancing real-time human detection based on histograms of oriented gradients

AuthorsPedersoli, Marco; Gonzàlez, Jordi; Chakraborty, Bhaskar; Villanueva, Juan J.
KeywordsPattern recognition: Computer vision
Computer vision
Issue Date2007
CitationComputer Recognition Systems 2: 739-746 (2007)
SeriesAdvances in Soft Computing 45
AbstractIn this paper we propose a human detection framework based on an enhanced version of Histogram of Oriented Gradients (HOG) features. These feature descriptors are computed with the help of a precalculated histogram of square-blocks. This novel method outperforms the integral of oriented histograms allowing the calculation of a single feature four times faster. Using Adaboost for HOG feature selection and Support Vector Machine as weak classifier, we build up a real-time human classifier with an excellent detection rate.
DescriptionPresentado al CORES-2007 celebrado en Wroclaw (Poland).
Publisher version (URL)http://dx.doi.org/10.1007/978-3-540-75175-5_91
Appears in Collections:(IRII) Libros y partes de libros
Files in This Item:
File Description SizeFormat 
Enhancing real-time.pdf156,9 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.