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  4. Vol 1, Issue 1, 2022

Siamese Network for Fast Visual Tracking of Rotating Targets

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DOI: 10.23977/vcip.2022.010101 | Downloads: 11 | Views: 1160

Author(s)

Yibo Gao 1

Affiliation(s)

1 Guidance Control and Information Perception Laboratory of High Overload Ammunition, Army Artillery and Air Defense Academy of PLA, Hefei, Anhui, 230031, China

Corresponding Author

Yibo Gao

ABSTRACT

Directional target tracking is an important task in the field of target tracking, which has great application prospects in geography, agriculture and military. The current algorithm for rotating target detection relies on the detection frame after regression and then uses the segmentation mask for further accuracy, which is obviously too cumbersome. In this paper, a scheme of direct generation of directional detection frame (Siamese-ORPN) is proposed. Specifically, improve the alternative box strategy so that the orpn can directly generate a high-quality directional detection box proposal in a low consumption manner. In addition, a top-down feature fusion network is proposed as the backbone of feature extraction and feature fusion, which can obtain substantial benefits from the diversity of visual semantic levels. Siamese-ORPN realizes lightweight and real-time detection, and achieves leading performance on benchmark data sets, including vot2018 (44.6% EAO) and vot2019 (39.6% EAO).

KEYWORDS

Oriented target tracking, feature extraction, RPN, Feature fusion

CITE THIS PAPER

Yibo Gao, Siamese Network for Fast Visual Tracking of Rotating Targets. Visual Communications and Image Processing (2022) Vol. 1: 1-7. DOI: http://dx.doi.org/10.23977/vcip.2022.010101.

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