Visual Target Locking during Fast Ground Maneuver using Enhanced ORB Predictive Particle Filter

Heru Taufiqurrohman, Abdul Muis, Yusuf Nur Wijayanto, Tsani Hendro Nugroho, Dito Eka Cahya, Zaid Cahya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Maintaining the visual lock on a target during rapid ground maneuvers is critical for various applications, including autonomous vehicles, robotics, and defense systems. Existing visual tracking algorithms face challenges in maintaining accurate and reliable target locks in dynamic and unpredictable maneuvers, especially on previously unknown targets. One technique developed to address this issue is the ORB-enhanced particle filter (ORBPF). However, ORBPF is unable to handle quick maneuvers because the prediction method uses a constant velocity (CV) dynamic model. This research focuses on addressing the limitations of existing ORBPF tracking algorithms for fast ground maneuver objects using the constant-velocity and constant-turn (CVCT) dynamic model approach to predict the next movement. By incorporating motion prediction into the current ORBPF framework, the proposed system anticipates future target positions and adaptively adjusts tracking parameters to maintain stable locking. Functional testing was performed using an object tracking benchmark to compare ORBPF-CVCT with standard ORBPF in specific scenarios. Results show that the standard ORBPF-CV achieved RMSE up to 345,518 px while our proposed ORBPF-CVCT achieved up to 191,387 px. These results show that the proposed method is able to track fast maneuver objects better than the previous ORBPF method.

Original languageEnglish
Title of host publicationProceeding - 2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications
Subtitle of host publicationEmpowering Global Progress: Innovative Electronic and Telecommunication Solutions for a Sustainable Future, ICRAMET 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-72
Number of pages6
ISBN (Electronic)9798350343892
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2023 - Virtual, Online, Indonesia
Duration: 15 Nov 202316 Nov 2023

Publication series

NameProceeding - 2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications: Empowering Global Progress: Innovative Electronic and Telecommunication Solutions for a Sustainable Future, ICRAMET 2023

Conference

Conference2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2023
Country/TerritoryIndonesia
CityVirtual, Online
Period15/11/2316/11/23

Keywords

  • Ground Maneuver
  • Motion predictions
  • ORB
  • Particle Filter
  • Visual Object Tracking

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