Double Phase Pedestrian Detection with Minimal Number of False Positives per Image
Double Phase Pedestrian Detection with Minimal Number of False Positives per Image
复制标题
双阶段行人检测，每张图像的误报数量最少
DOI：
10.1145/3070617.3070642
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Miryong Park
中科院分区：
文献类型：
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作者：
Masoud Afrakhteh;Miryong Park
在本文中，我们以一种减少每帧误报（FPs）数量的方式研究了从可见彩色图像中检测行人。我们提出了一种简单的方法来消除许多这种不必要的FPs，这些FPs通常是由于将最先进的行人物体检测器应用于可见彩色图像而导致的。行人身体的对称结构往往可以作为区分行人和非行人的一个很好的线索。因此，在检测的初始步骤中，每一个单独的检测对象（有界框）都被用来重建一些新的对称外观的对象。如果检测到这些物体中的任何一个，则确认它们是一个人；否则，它们将从检测对象的第一个列表中省略。实验结果表明，如何使用这种简单的技术去除这些FPs，同时保持先前的低缺失率。
In this paper, we investigate pedestrian detection from visible color imagery in a manner that reduces the number of false positives (FPs) per frame. We propose a simple way to eliminate many of such unwanted FPs that usually result from applying a state-of-the-art pedestrian object detector to a visible color image. The symmetric structure of pedestrian bodies can often be a good clue to distinguish them from non-pedestrians. Hence, each and every individual detected object (bounded box) in the initial step of detection is used to reconstruct some new symmetric-looking objects. If any of these objects are detected, they are confirmed to be a person; otherwise, they are omitted from the very first list of detected objects. Experimental results show how these FPs are removed using such a simple technique while maintaining the previous low miss rate.