Infrared target tracking based on transformer

Zhou Xi; Xiaohong Li

doi:10.1117/12.2682473

20 June 2023 Infrared target tracking based on transformer

Zhou Xi, Xiaohong Li

Proceedings Volume 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023); 127150R (2023) https://doi.org/10.1117/12.2682473
Event: Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 2023, Dalian, China

Abstract

Infrared target images have low signal-to-noise ratio, blurred edges and missing textures, which make it a great challenge to identify the target and achieve stable tracking in the tracking process. However, ordinary target trackers use feature fusion as a convolutional operation, which is a local matching process that easily leads to the absence of high-level semantic information of the image, and is further limited on infrared images. Inspired by transformer, its attention mechanism can capture global features, as well as contextual relationships between features, and can well establish the association between remote features , long-range dependency and other advantages, we designed transofmer-based infrared target tracker, which is a network that performs feature enhancement and fusion on infrared images by tranformer, and classifies and regresses targets by classification head, and has proved the effectiveness of the method by conducting extensive experiments on challenging benchmarks.

Citation Download Citation

Zhou Xi and Xiaohong Li "Infrared target tracking based on transformer", Proc. SPIE 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 127150R (20 June 2023); https://doi.org/10.1117/12.2682473

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KEYWORDS

Infrared imaging

Infrared search and track

Thermography

Education and training

Transformers

Optical tracking

Computer vision technology

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