基于深度学习的视觉跟踪算法研究综述

视觉跟踪是计算机视觉的重要研究领域之一。传统的视觉跟踪算法难以很好地解决复杂背景中的跟踪问题,如光线变化、目标发生较大的尺寸和姿态变化或目标被遮挡等。而深度学习的引入为视觉跟踪研究开辟了新的途径。但目前国内外基于深度学习的视觉跟踪研究文献相对较少,为 吸引更多视觉跟踪领域研究者对深度学习进行探索和讨论,并推动视觉跟踪算法的研究,简要介绍了视觉跟踪和深度学习的研究现状,重点分析了基于深度学习的视觉跟踪算法的相关文献,讨论了各算法的优缺点,最后提出了进一步研究的方向以及对基于深度学习的视觉跟踪算法的展望。

Survey on Visual Tracking Algorithms Based on Deep Learning Technologies

Visual tracking is a fundamental subject in the field of computer vision.Classical tracking methods are not good at handling the problems of the complex background,such as illumination variation,great change of the target size and posture change greatly or occlusion and so on.Meanwhile,the introduction of deep learning technologies opens a new way of visual tracking study.There are a few research literature on visual tracking based on deep learning relatively,both in China and abroad at present.In order to attract more researchers in the field of visual tracking to explore and discuss deep learning,and to promote the research of visual tracking algorithm,this overview briefly reviewed the research status of visual tracking and deep learning.Then we focused on the related literatures about algorithms of visual tracking based on deep learning,and discussed their advantages and disadvantages.Finally,we proposed the direction of further research and the prospect of visual tracking algorithm based on deep learning.