论文标题

在阻塞下对面部识别技术的调查

A survey of face recognition techniques under occlusion

论文作者

Zeng, Dan, Veldhuis, Raymond, Spreeuwers, Luuk

论文摘要

在遮挡下识别面孔的能力有限是一个长期存在的问题,它对面部识别系统甚至人类都带来了独特的挑战。与其他挑战(例如姿势变化,不同表达式等)相比,研究的问题越来越少。然而,必须利用对现实世界应用的面部识别的全部潜力。在本文中,我们将范围限制为遮挡的面部识别。首先,我们探讨了遮挡问题是什么以及可能出现什么固有困难。作为本评论的一部分,我们在闭塞下引入了面部检测,这是面部识别的初步步骤。其次,我们介绍了现有的面部识别方法如何应对遮挡问题并将其分为三类,即1)闭塞鲁棒特征提取方法,2)闭塞意识到的面部识别方法和3)基于遮挡恢复的面部识别方法。此外,我们分析了比较代表性方法的动机,创新,利弊。最后,对未来的挑战和方法趋势进行了彻底讨论。

The limited capacity to recognize faces under occlusions is a long-standing problem that presents a unique challenge for face recognition systems and even for humans. The problem regarding occlusion is less covered by research when compared to other challenges such as pose variation, different expressions, etc. Nevertheless, occluded face recognition is imperative to exploit the full potential of face recognition for real-world applications. In this paper, we restrict the scope to occluded face recognition. First, we explore what the occlusion problem is and what inherent difficulties can arise. As a part of this review, we introduce face detection under occlusion, a preliminary step in face recognition. Second, we present how existing face recognition methods cope with the occlusion problem and classify them into three categories, which are 1) occlusion robust feature extraction approaches, 2) occlusion aware face recognition approaches, and 3) occlusion recovery based face recognition approaches. Furthermore, we analyze the motivations, innovations, pros and cons, and the performance of representative approaches for comparison. Finally, future challenges and method trends of occluded face recognition are thoroughly discussed.

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