An autonomous visual tracking algorithm based on mean-shift algorithm and extended Kalman filter estimator

Narsimlu Kemsaram, T.V. Rajini Kanth, Devendra Rao Guntupalli, Anil Kuvvarapu

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

An autonomous visual tracking algorithm based on mean-shift and extended
kalman filter is proposed for micro aerial vehicle. This proposed algorithm is
incorporated in the autonomous visual tracking software. This proposed
algorithm identifies and tracks the ground moving target based on its 2D
color space histogram. The implemented proposed algorithm is included in
simulation to check whether the proposed algorithm identifies and tracks
the GMT accurately or not from micro aerial vehicle. The captured results
prove that the proposed autonomous visual tracking algorithm identifies and
tracks the GMT very accurately.
Original languageEnglish
Pages (from-to)14-23
Number of pages10
JournalInternational Journal of Innovative Computer Science & Engineering
Volume3
Issue number2
Publication statusPublished - Apr 2016
Externally publishedYes

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abstract = "An autonomous visual tracking algorithm based on mean-shift and extendedkalman filter is proposed for micro aerial vehicle. This proposed algorithm isincorporated in the autonomous visual tracking software. This proposedalgorithm identifies and tracks the ground moving target based on its 2Dcolor space histogram. The implemented proposed algorithm is included insimulation to check whether the proposed algorithm identifies and tracksthe GMT accurately or not from micro aerial vehicle. The captured resultsprove that the proposed autonomous visual tracking algorithm identifies andtracks the GMT very accurately.",
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An autonomous visual tracking algorithm based on mean-shift algorithm and extended Kalman filter estimator. / Kemsaram, Narsimlu; Rajini Kanth, T.V.; Guntupalli, Devendra Rao; Kuvvarapu, Anil.

In: International Journal of Innovative Computer Science & Engineering, Vol. 3, No. 2, 04.2016, p. 14-23.

Research output: Contribution to journalArticleAcademicpeer-review

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