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Integral Channel Features

Dollár, Piotr and Tu, Zhuowen and Perona, Pietro and Belongie, Serge (2009) Integral Channel Features. In: Proceedings of the British Machine Vision Conference. BMVC Press , London, 91.1-91.11. ISBN 1-901725-39-1. https://resolver.caltech.edu/CaltechAUTHORS:20150903-113325911

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Abstract

We study the performance of ‘integral channel features’ for image classification tasks, focusing in particular on pedestrian detection. The general idea behind integral channel features is that multiple registered image channels are computed using linear and non-linear transformations of the input image, and then features such as local sums, histograms, and Haar features and their various generalizations are efficiently computed using integral images. Such features have been used in recent literature for a variety of tasks – indeed, variations appear to have been invented independently multiple times. Although integral channel features have proven effective, little effort has been devoted to analyzing or optimizing the features themselves. In this work we present a unified view of the relevant work in this area and perform a detailed experimental evaluation. We demonstrate that when designed properly, integral channel features not only outperform other features including histogram of oriented gradient (HOG), they also (1) naturally integrate heterogeneous sources of information, (2) have few parameters and are insensitive to exact parameter settings, (3) allow for more accurate spatial localization during detection, and (4) result in fast detectors when coupled with cascade classifiers.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.5244/C.23.91DOIArticle
http://www.bmva.org/bmvc/2009/Papers/Paper244/Paper244.htmlPublisherArticle
ORCID:
AuthorORCID
Perona, Pietro0000-0002-7583-5809
Additional Information:© 2009. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. S.B. work supported by NSF CAREER Grant #0448615 and ONR MURI Grant #N00014-08-1-0638.
Funders:
Funding AgencyGrant Number
NSF0448615
Office of Naval Research (ONR)N00014-08-1-0638
Record Number:CaltechAUTHORS:20150903-113325911
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20150903-113325911
Official Citation:Piotr Dollar, Zhuowen Tu, Pietro Perona and Serge Belongie. Integral Channel Features. In A. Cavallaro, S. Prince and D. Alexander, editors, Proceedings of the British Machine Conference, pages 91.1-91.11. BMVA Press, September 2009. doi:10.5244/C.23.91.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:60048
Collection:CaltechAUTHORS
Deposited By: Caroline Murphy
Deposited On:15 Sep 2015 00:19
Last Modified:03 Oct 2019 08:53

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