Thermal Infrared Tracking using Multi-stages Deep Features Fusion

doi:10.1109/CCDC49329.2020.9164750

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 空间光学应用研究室

	Thermal Infrared Tracking using Multi-stages Deep Features Fusion
	Zhang, Ximing 1; Chen, Rongli 1; Liu, Gang 1; Li, Xuyang 1; Luo, Shujuan 2; Fan, Xuewu 1
	2020-08
会议日期	2020-08-22
会议地点	Hefei, China
关键词	Thermal Infrared Tracking Multi-stages Networks Deep Features Fusion Siamese Networks Region Proposal Networks
DOI	10.1109/CCDC49329.2020.9164750
页码	1883-1888
英文摘要	Thermal infrared (TIR) tracking can be utilized to track the target in the images generated by thermal infrared sensors due to the weak influence by illumination changes. However, there are still some challenges to do thermal infrared tracking when suffering drastic appearance variation, heavy occlusion and background clutters. The absence of RGB patterns and low resolution also constrain the tracking performance in complex scenarios. The deep convolutional features are widely utilized to solve visual tracking problems which successfully extracted the spatial and semantic information though object representation. Motivated by these methods, we firstly propose to combine multi-stages cascaded Siamese networks to achieve deep features fusion in three stages, then achieve the tracking procedure by candidates matching strategy. The final results are obtained by non-maximum suppression and scale penalty. The proposed method can inherit the advantages by fusing multi-stages deep features and achieve end-to-end learning simultaneously. The experiments are evaluated with state-of-the-art methods on VOT-TIR2016 benchmark and attributes based comparison. The tracking results demonstrate that our proposed method outperforms the compared methods in terms of accuracy and robustness. © 2020 IEEE.
产权排序	1
会议录	Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
会议录出版者	Institute of Electrical and Electronics Engineers Inc., United States
语种	英语
ISBN号	9781728158549
内容类型	会议论文
源URL	[http://ir.opt.ac.cn/handle/181661/93722]
专题	西安光学精密机械研究所_空间光学应用研究室
作者单位	1.Institute of Optics and Precision Mechanics of CAS, Xi'an; 710119, China; 2.Northwestern Polytechnical University, Academy of Astronautics, Xi'an; 710072, China
推荐引用方式 GB/T 7714	Zhang, Ximing,Chen, Rongli,Liu, Gang,et al. Thermal Infrared Tracking using Multi-stages Deep Features Fusion[C]. 见:. Hefei, China. 2020-08-22.