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Implementation of object recognition and tracking algorithm on real-time basis

descriptionPublicationkeyboard_double_arrow_right Article 01 Jul 2013Publisher:IEEEJournal:Eurocon 2013
Authors: Jae Chang Kwak; Tae Ryong Park; Yong Seo Koo; Kwang Yeob Lee;

doi: 10.1109/eurocon.2013.6625254

Implementation of object recognition and tracking algorithm on real-time basis

Abstract

This paper is intended to recognize and track objects on real time basis under the embedded environment. Speed and rate of recognition have been improved by strong directional SURF and optical flow, but its speed is not fast enough for the embedded system. In this paper, recognition and tracking objects by integration of ORB and optical flow with a parallelization using OpenMP are implemented. The result shows an improved processing speed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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