SiamPRA: An Effective Network for UAV Visual Tracking
| Autor: | Jiafeng Li, Kang Zhang, Zheng Gao, Liheng Yang, Li Zhuo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
History
Polymers and Plastics Computer Networks and Communications Hardware and Architecture Control and Systems Engineering object tracking attention mechanism network compression embedded vision system Signal Processing Electrical and Electronic Engineering Business and International Management Industrial and Manufacturing Engineering |
| Zdroj: | Electronics; Volume 12; Issue 11; Pages: 2374 |
| ISSN: | 2079-9292 |
| DOI: | 10.3390/electronics12112374 |
| Popis: | The visual navigation system is an important module in intelligent unmanned aerial vehicle (UAV) systems as it helps to guide them autonomously by tracking visual targets. In recent years, tracking algorithms based on Siamese networks have demonstrated outstanding performance. However, their application to UAV systems has been challenging due to the limited resources available in such systems.This paper proposes a simple and efficient tracking network called the Siamese Pruned ResNet Attention (SiamPRA) network and applied to embedded platforms that can be deployed on UAVs. SiamPRA is base on the SiamFC network and incorporates ResNet-24 as its backbone. It also utilizes the spatial-channel attention mechanism, thereby achieving higher accuracy while reducing the number of computations. Further, sparse training and pruning are used to reduce the size of the model while maintaining high precision. Experimental results on the challenging benchmarks VOT2018, UAV123 and OTB100 show that SiamPRA has a higher accuracy and lower complexity than other tracking networks. |
| Databáze: | OpenAIRE |
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