Learning Multidimensional Spatial Attention for Robust Nighttime Visual Tracking

IF 3.2 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Qi Gao;Mingfeng Yin;Yuanzhi Ni;Yuming Bo;Shaoyi Bei
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引用次数: 0

Abstract

The recent development of advanced trackers, which use nighttime image enhancement technology, has led to marked advances in the performance of visual tracking at night. However, the images recovered by currently available enhancement methods still have some weaknesses, such as blurred target details and obvious image noise. To this end, we propose a novel method for learning multidimensional spatial attention for robust nighttime visual tracking, which is developed over a spatial channel transformer based low light enhancer (SCT), named MSA-SCT. First, a novel multidimensional spatial attention (MSA) is designed. Additional reliable feature responses are generated by aggregating channel and multi-scale spatial information, thus making the model more adaptable to illumination conditions and noise levels in different regions of the image. Second, with optimized skip connections, the effects of redundant information and noise can be limited, which is more useful for the propagation of fine detail features in nighttime images from low to high level features and improves the enhancement effect. Finally, the tracker with enhancers was tested on multiple tracking benchmarks to fully demonstrate the effectiveness and superiority of MSA-SCT.
学习多维空间注意力,实现稳健的夜间视觉跟踪
近年来,利用夜间图像增强技术的先进跟踪器的开发,使夜间视觉跟踪的性能有了显著提高。然而,目前可用的增强方法所恢复的图像仍存在一些缺陷,如目标细节模糊、图像噪声明显等。为此,我们提出了一种学习多维空间注意力的新方法,用于实现稳健的夜间视觉跟踪,该方法是在基于空间通道变换器的微光增强器(SCT)上开发的,命名为 MSA-SCT。首先,设计了一种新型多维空间注意力(MSA)。通过聚合信道和多尺度空间信息,产生更多可靠的特征响应,从而使模型更能适应图像不同区域的光照条件和噪声水平。其次,通过优化跳转连接,可以限制冗余信息和噪声的影响,这更有利于夜间图像中精细细节特征从低级特征向高级特征的传播,并提高增强效果。最后,对带有增强器的跟踪器进行了多个跟踪基准测试,以充分展示 MSA-SCT 的有效性和优越性。
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来源期刊
IEEE Signal Processing Letters
IEEE Signal Processing Letters 工程技术-工程:电子与电气
CiteScore
7.40
自引率
12.80%
发文量
339
审稿时长
2.8 months
期刊介绍: The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.
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