dc.contributor.author | Bilgic, Berkin | |
dc.contributor.author | Horn, Berthold Klaus Paul | |
dc.contributor.author | Masaki, Ichiro | |
dc.date.accessioned | 2012-07-30T13:15:21Z | |
dc.date.available | 2012-07-30T13:15:21Z | |
dc.date.issued | 2010-08 | |
dc.date.submitted | 2010-05 | |
dc.identifier.isbn | 978-1-4244-7866-8 | |
dc.identifier.issn | 1931-0587 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/71884 | |
dc.description.abstract | We investigate a fast pedestrian localization framework that integrates the cascade-of-rejectors approach with the Histograms of Oriented Gradients (HoG) features on a data parallel architecture. The salient features of humans are captured by HoG blocks of variable sizes and locations which are chosen by the AdaBoost algorithm from a large set of possible blocks. We use the integral image representation for histogram computation and a rejection cascade in a sliding-windows manner, both of which can be implemented in a data parallel fashion. Utilizing the NVIDIA CUDA framework to realize this method on a Graphics Processing Unit (GPU), we report a speed up by a factor of 13 over our CPU implementation. For a 1280×960 image our parallel technique attains a processing speed of 2.5 to 8 frames per second depending on the image scanning density, which is similar to the recent GPU implementation of the original HoG algorithm in. | en_US |
dc.language.iso | en_US | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.isversionof | http://dx.doi.org/ 10.1109/IVS.2010.5548145 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | IEEE | en_US |
dc.title | Fast Human Detection With Cascaded Ensembles On The GPU | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Bilgic, Berkin, Berthold K.P. Horn, and Ichiro Masaki. “Fast Human Detection with Cascaded Ensembles on the GPU.” IEEE, 2010. 325–332. © Copyright 2010 IEEE | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.contributor.approver | Horn, Berthold K. P. | |
dc.contributor.mitauthor | Bilgic, Berkin | |
dc.contributor.mitauthor | Horn, Berthold Klaus Paul | |
dc.contributor.mitauthor | Masaki, Ichiro | |
dc.relation.journal | 2010 IEEE Intelligent Vehicles Symposium (IV) | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
dspace.orderedauthors | Bilgic, Berkin; Horn, Berthold K.P.; Masaki, Ichiro | en |
dc.identifier.orcid | https://orcid.org/0000-0003-3434-391X | |
dc.identifier.orcid | https://orcid.org/0000-0002-6657-5646 | |
mit.license | PUBLISHER_POLICY | en_US |
mit.metadata.status | Complete | |