我们可以使用预处理来提高Viola-Jones人脸检测器的性能吗？实证研究
Can We Boost the Power of the Viola-Jones Face Detector Using Pre-processing? An Empirical Study
摘要：
Viola-Jones人脸检测算法曾经是（现在仍然是）一个非常流行的人脸检测器。尽管最近提出了许多人脸检测技术，但由于Viola-Jones算法的简单性，仍有许多研究工作基于Viola-Jones算法。本文研究了一组盲预处理方法对Viola-Jones算法人脸检测率的影响。我们专注于两个方面的改进，特别是照明不良的脸和模糊的脸。为了提高检测精度，采用了多种光照不变性和去模糊的方法。我们希望避免使用可能阻碍人脸检测器的盲预处理方法。为此，我们进行了两组实验。执行第一组以避免可能损害面部检测器的任何盲预处理方法。执行第二组以研究所选预处理方法对遭受硬条件的图像的影响。我们提出了两种方式的预处理方法应用于图像之前，被使用的Viola-Jones人脸检测器。四个不同的数据集被用来得出一个连贯的结论，潜在的改善所造成的使用先前的增强图像。实验结果表明，某些预处理方法可能会影响Viola-Jones人脸检测算法的准确性。然而，其他预处理方法对人脸检测器的准确性有明显的积极影响。总的来说，我们推荐三种简单快速的盲光度归一化方法作为预处理步骤，以提高预训练的Viola-Jones人脸检测器的准确性。
英文摘要：
The Viola-Jones face detection algorithm was (and still is) a quite popular face detector. In spite of the numerous face detection techniques that have been recently presented, there are many research works that are still based on the Viola-Jones algorithm because of its simplicity. In this paper, we study the influence of a set of blind pre-processing methods on the face detection rate using the Viola-Jones algorithm. We focus on two aspects of improvement, specifically badly illuminated faces and blurred faces. Many methods for lighting invariant and deblurring are used in order to improve the detection accuracy. We want to avoid using blind pre-processing methods that may obstruct the face detector. To that end, we perform two sets of experiments. The first set is performed to avoid any blind pre-processing method that may hurt the face detector. The second set is performed to study the effect of the selected pre-processing methods on images that suffer from hard conditions. We present two manners of applying the pre-processing method to the image prior to being used by the Viola-Jones face detector. Four different datasets are used to draw a coherent conclusion about the potential improvement caused by using prior enhanced images. The results demonstrate that some of the pre-processing methods may hurt the accuracy of Viola-Jones face detection algorithm. However, other pre-processing methods have an evident positive impact on the accuracy of the face detector. Overall, we recommend three simple and fast blind photometric normalization methods as a pre-processing step in order to improve the accuracy of the pre-trained Viola-Jones face detector.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
