Relocation with Coverage and Intersection over Union Loss for Target Matching

Zejin Lu, Zejin Lu, Jinqi Liao, Jiyang Lv, Fengjun Chen, Fengjun Chen

2021

Abstract

Target matching is a common task in the field of computer vision, which has a wide range of implements in the fields of target tracking, medical image analysis, robot navigation, etc. The tasks in these scenarios have high requirements for locating accuracy, reliability and robustness, but the existing methods cannot meet these requirements. To improve the algorithm performance in these aspects, a novel practical target matching framework is proposed in this paper. We firstly present a new bounding box regression metric called Coverage-Intersection over Union (Co-IoU) to obtain higher positioning accuracy performance compared to previous bounding regression strategies. Also, a reasonable region validation and filter strategy is proposed to reduce the false positive matches and the Region of Interest (ROI) adjustment and relocation matching strategy are innovatively present to acquire higher locating accuracy. Our experiments show that the proposed framework is more robust, accurate and reliable than the previous relevant algorithms. Besides, Coverage-Intersection over Union Loss and relocation strategy proposed in this paper can significantly improve the performance of the general object detector as well.

Paper Citation

in Harvard Style

Lu Z., Liao J., Lv J. and Chen F. (2021). Relocation with Coverage and Intersection over Union Loss for Target Matching. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6, SciTePress, pages 253-260. DOI: 10.5220/0010191802530260

in Bibtex Style

@conference{visapp21,
author={Zejin Lu and Jinqi Liao and Jiyang Lv and Fengjun Chen},
title={Relocation with Coverage and Intersection over Union Loss for Target Matching},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={253-260},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010191802530260},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Relocation with Coverage and Intersection over Union Loss for Target Matching
SN - 978-989-758-488-6
AU - Lu Z.
AU - Liao J.
AU - Lv J.
AU - Chen F.
PY - 2021
SP - 253
EP - 260
DO - 10.5220/0010191802530260
PB - SciTePress