SiamHAS:姆追踪器具有层次注意力战略,用于空中追踪
Faxue Liu1,2, Jinghong Liu1,2, Qiqi Chen1,2
1Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP), Chinese Academy of Sciences, Changchun 130033, China.
Micromachines
|July 8, 2023
概括
本研究介绍了SiamHAS,这是一款新的语追踪器,使用变压器增强和层次关注来增强多层次功能. 这种方法提高了空中视觉跟踪的准确性,特别是在具有挑战性的条件下,如遮蔽和尺度变化.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 基于罗网络的追踪器在空中场景中经常遭受跟踪漂移的困扰,原因是多层次特征的不充分利用.
- 挑战包括目标封闭,尺度变化和低分辨率跟踪,导致视觉跟踪的精度降低.
研究的目的:
- 为了提高姆追踪器在具有挑战性的空中视觉追踪场景中的性能.
- 为解决因功能利用不完善而导致的跟踪漂移和低准确性问题.
主要方法:
- 提出了一个罗式追踪器,结合了变压器多层次功能增强.
- 引入一个层次关注策略,以适应性地专注于目标地区信息.
- 使用变压器多级增强来提高提取的特征的突出性.
主要成果:
- 在UVA123,UAV20L和OTB100数据集上进行了广泛的实验.
- 拟议的SiamHAS追踪器与最先进的追踪器相比表现良好.
- 在具有挑战性的空中追踪场景中观察到显著的改善.
结论:
- SiamHAS追踪器有效地增强了多层次的功能,并适应地利用目标信息.
- 拟议的方法在具有挑战性的空中视觉跟踪任务中表现出卓越的性能.
- 层次化的注意力策略对于提高跟踪稳定性和准确性至关重要.
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