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Abstracts: Online Supplements Volume 12, Number 1s Volume 12, Number 2s

Abstracts: Online Supplements Volume 12, Number 1s Volume 12, Number 2s In order to speed up the publication process, we have begun to publish supplemental online-only issues. The following abstracts describe the articles in Vol. 12(1s) and 12(2s). These articles are available in the Digital Library. DOI:http://dx.doi.org/10.1145/2485984.2485985 Volume 12, Number 1s Article 33: A Novel Low-Power Embedded Object Recognition System Working at Multi-Frames per Second ANTONIS NIKITAKIS, SAVVAS PAPAIOANNOU, and IOANNIS PAPAEFSTATHIOU, Technical University of Crete One very important challenge in the field of multimedia is the implementation of fast and detailed Object Detection and Recognition systems. In particular, in the current state-of-the-art mobile multimedia systems, it is highly desirable to detect and locate certain objects within a video frame in real time. Although a significant number of Object Detection and Recognition schemes have been developed and implemented, triggering very accurate results, the vast majority of them cannot be applied in state-of-the-art mobile multimedia devices; this is mainly due to the fact that they are highly complex schemes that require a significant amount of processing power, while they are also time consuming and very power hungry. In this article, we present a novel FPGA-based embedded implementation of a very efficient object recognition algorithm called Receptive Field Cooccurrence Histograms Algorithm http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Embedded Computing Systems (TECS) Association for Computing Machinery

Abstracts: Online Supplements Volume 12, Number 1s Volume 12, Number 2s

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2013 by ACM Inc.
ISSN
1539-9087
DOI
10.1145/2485984.2499550
Publisher site
See Article on Publisher Site

Abstract

In order to speed up the publication process, we have begun to publish supplemental online-only issues. The following abstracts describe the articles in Vol. 12(1s) and 12(2s). These articles are available in the Digital Library. DOI:http://dx.doi.org/10.1145/2485984.2485985 Volume 12, Number 1s Article 33: A Novel Low-Power Embedded Object Recognition System Working at Multi-Frames per Second ANTONIS NIKITAKIS, SAVVAS PAPAIOANNOU, and IOANNIS PAPAEFSTATHIOU, Technical University of Crete One very important challenge in the field of multimedia is the implementation of fast and detailed Object Detection and Recognition systems. In particular, in the current state-of-the-art mobile multimedia systems, it is highly desirable to detect and locate certain objects within a video frame in real time. Although a significant number of Object Detection and Recognition schemes have been developed and implemented, triggering very accurate results, the vast majority of them cannot be applied in state-of-the-art mobile multimedia devices; this is mainly due to the fact that they are highly complex schemes that require a significant amount of processing power, while they are also time consuming and very power hungry. In this article, we present a novel FPGA-based embedded implementation of a very efficient object recognition algorithm called Receptive Field Cooccurrence Histograms Algorithm

Journal

ACM Transactions on Embedded Computing Systems (TECS) – Association for Computing Machinery

Published: Jun 1, 2013

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