Computer Vision Center and the Computer Science Department, Universitat Autònoma deBarcelona, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain.
IEEE Trans Pattern Anal Mach Intell. 2010 Jul;32(7):1239-58. doi: 10.1109/TPAMI.2009.122.
Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appearance of pedestrians (e.g., different clothes, changing size, aspect ratio, and dynamic shape) and the unstructured environment, it is very difficult to cope with the demanded robustness of this kind of system. Two problems arising in this research area are the lack of public benchmarks and the difficulty in reproducing many of the proposed methods, which makes it difficult to compare the approaches. As a result, surveying the literature by enumerating the proposals one--after-another is not the most useful way to provide a comparative point of view. Accordingly, we present a more convenient strategy to survey the different approaches. We divide the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities. Then, the different proposed methods are analyzed and classified with respect to each processing stage, favoring a comparative viewpoint. Finally, discussion of the important topics is presented, putting special emphasis on the future needs and challenges.
高级驾驶辅助系统(ADAS),特别是行人保护系统(PPS),已成为一个活跃的研究领域,旨在提高交通安全。PPS 的主要挑战是开发可靠的车载行人检测系统。由于行人的外观变化多样(例如,不同的衣服、不断变化的大小、纵横比和动态形状)以及非结构化的环境,很难满足这种系统的稳健性要求。在这个研究领域中存在两个问题,即缺乏公共基准和难以复制许多提出的方法,这使得很难比较这些方法。因此,通过逐一列举提案来列举文献并不是提供比较观点的最有用方法。因此,我们提出了一种更方便的策略来调查不同的方法。我们将图像中的行人检测问题分为不同的处理步骤,每个步骤都有特定的职责。然后,根据每个处理阶段分析和分类不同的提出方法,有利于比较的观点。最后,提出了对重要主题的讨论,特别强调了未来的需求和挑战。