Development of Adaptive Tracking using Advance Filter and Selection Features Method

Authors

  • Ikhlas Watan Ghindawi University of Al-Mustansiriyah Bhagdad, Iraq
  • Lamyaa Mohammed Kadhim University of Al-Mustansiriyah Bhagdad, Iraq

DOI:

https://doi.org/10.31695/IJERAT.2022.8.10.1

Keywords:

Feature Selection, Kalman Filters, Object Detection, Object Tracking

Abstract

Recently, Kalman filter (KF)-based algorithms of tracking had demonstrated to be effective  However, their efficiency is limited by fixed feature selections and the possibility of model drift.  In the presented research, we offer a new adaptive feature selection-based tracking approach that maintains the KF’s excellent   discriminating power . Depending on scores of confidence regarding features in every one of frames, the suggested approach might select (automatically) either SIFT feature or the colour feature for the tracking . With a use of KF, a response map related to the SIFT features and color features are retrieved first . The color features that distinguish the luminance from the color are extracted using the Lab color space . Second, the average peak-to-correlation energy is used for the determination of the confidence region and the target's possible location  . Finally, a total of 3 criteria have been utilized in order to choose the appropriate feature for present frame in order to execute adaptive tracking . On OTB benchmark datasets, the experimental findings show that the suggested tracker performs better in comparison with other state-of-art techniques

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Published

2022-10-17

How to Cite

Development of Adaptive Tracking using Advance Filter and Selection Features Method. (2022). International Journal of Engineering Research and Advanced Technology (ijerat) (E-ISSN 2454-6135) , 8(10), 1-10. https://doi.org/10.31695/IJERAT.2022.8.10.1