Work

Robust planar object tracking using SIFT and GHT with spatial locality

Year: 2024

Type: article

Abstract: Planar object tracking (POT) is crucial in vision‐based robotic applications. Despite significant advancements, tracking planar objects under real‐world conditions remains a challenge owing to various factors. The method proposed by the authors leverages SIFT features and generalized Hough transform, which is enhanced by spatial locality, to mitigate background clutter and false matching. The experimental results demonstrate that this method significantly outperforms existing approaches, achieving higher precision across various alignment error thresholds.

Source: Electronics Letters

DOI: 10.1049/ell2.70035

Authors: Suwon Lee, Sang‐Min Choi

Institution: Gyeongsang National University

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,540

Funders: National Research Foundation, Ministry of Education, National Research Foundation of Korea, Ministry of Education, India