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author:

You, Yue (You, Yue.) [1] | Wang, Yihong (Wang, Yihong.) [2] | Cai, Yu (Cai, Yu.) [3] | Zhu, Mingzhu (Zhu, Mingzhu.) [4] | He, Bingwei (He, Bingwei.) [5]

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EI

Abstract:

A novel event sensor-based object localization method is proposed in this paper. It addresses the accuracy limitations of event sensors caused by their limited spatial resolution and binary grayscale levels. The method uses flickering beacons and replaces the event camera's lens with a mask printed with a marker field. This configuration distributes location-coded events across the entire sensor instead of confining them to a small region, as in traditional methods. Major algorithms, including pattern simulation and optimized matching, are designed to achieve 3D localization and pose estimation. Experiments show a 17.3% accuracy improvement over state-of-the-art event-based methods in average translation error, consistent across varying distances and angles. This demonstrates its suitability for surgical navigation, virtual reality, and other precise, real-time localization tasks. © 2025 Elsevier Inc.

Keyword:

3D modeling Camera lenses Local binary pattern Pattern matching Virtual reality

Community:

  • [ 1 ] [You, Yue]School of Mechanical Engineering and Automation, Fuzhou University, Fujian, Fuzhou; 350108, China
  • [ 2 ] [Wang, Yihong]Department of Otorhinolaryngology, Fujian Provincial Hospital, Fujian, Fuzhou; 350108, China
  • [ 3 ] [Cai, Yu]School of Mechanical Engineering and Automation, Fuzhou University, Fujian, Fuzhou; 350108, China
  • [ 4 ] [Zhu, Mingzhu]School of Mechanical Engineering and Automation, Fuzhou University, Fujian, Fuzhou; 350108, China
  • [ 5 ] [He, Bingwei]School of Mechanical Engineering and Automation, Fuzhou University, Fujian, Fuzhou; 350108, China

Reprint 's Address:

  • [zhu, mingzhu]school of mechanical engineering and automation, fuzhou university, fujian, fuzhou; 350108, china;;

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Source :

Digital Signal Processing: A Review Journal

ISSN: 1051-2004

Year: 2025

Volume: 161

2 . 9 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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