论文标题
从手工制作到深度特征以供行人检测：一项调查
From Handcrafted to Deep Features for Pedestrian Detection: A Survey
论文作者
论文摘要
在计算机视觉中，行人检测是一个重要但具有挑战性的问题，尤其是在以人为本的任务中。在过去的十年中，在手工制作的功能和深度功能的帮助下，已经看到了重大改进。在这里，我们对行人检测的最新进展进行了全面的调查。首先，我们对单光线行人检测进行了详细的评论，其中包括基于手工特征的方法和基于深度特征的方法。对于基于手工特征的方法，我们对方法进行了广泛的审查，并发现具有较大自由度的手工制作功能具有更好的性能。在基于深度功能的方法的情况下，我们将其分为基于CNN的方法，以及采用手工制作和CNN功能的方法。我们给出了这些方法的统计分析和趋势，其中功能增强，部分感知和后处理方法吸引了主要关注。除了单光谱的行人检测外，我们还回顾了多光谱的行人检测，该检测为照明方差提供了更强大的功能。此外，我们介绍了一些相关的数据集和评估指标，并比较了一些代表性方法。我们通过强调需要解决的开放问题并突出未来的各个方向来结束这项调查。研究人员可以在https://github.com/jialecao001/pedsurvey上跟踪最新列表。
Pedestrian detection is an important but challenging problem in computer vision, especially in human-centric tasks. Over the past decade, significant improvement has been witnessed with the help of handcrafted features and deep features. Here we present a comprehensive survey on recent advances in pedestrian detection. First, we provide a detailed review of single-spectral pedestrian detection that includes handcrafted features based methods and deep features based approaches. For handcrafted features based methods, we present an extensive review of approaches and find that handcrafted features with large freedom degrees in shape and space have better performance. In the case of deep features based approaches, we split them into pure CNN based methods and those employing both handcrafted and CNN based features. We give the statistical analysis and tendency of these methods, where feature enhanced, part-aware, and post-processing methods have attracted main attention. In addition to single-spectral pedestrian detection, we also review multi-spectral pedestrian detection, which provides more robust features for illumination variance. Furthermore, we introduce some related datasets and evaluation metrics, and compare some representative methods. We conclude this survey by emphasizing open problems that need to be addressed and highlighting various future directions. Researchers can track an up-to-date list at https://github.com/JialeCao001/PedSurvey.
