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Face Detection in Repeated Settings

2019-03-20 05:03:27
Mohammad Nayeem Teli, Bruce A. Draper, J. Ross Beveridge

Abstract

Face detection is an important first step before face verification and recognition. In unconstrained settings it is still an open challenge because of the variation in pose, lighting, scale, background and location. However, for the purposes of verification we can have a control on background and location. Images are primarily captured in places such as the entrance to a sensitive building, in front of a door or some location where the background does not change. We present a correlation based face detection algorithm to detect faces in such settings, where we control the location, and leave lighting, pose, and scale uncontrolled. In these scenarios the results indicate that our algorithm is easy and fast to train, outperforms Viola and Jones face detection accuracy and is faster to test.

Abstract (translated)

人脸检测是人脸验证和识别的重要第一步。在不受约束的设置中,由于姿势、灯光、比例、背景和位置的变化,这仍然是一个开放的挑战。但是,为了进行验证,我们可以控制背景和位置。图像主要拍摄在敏感建筑物的入口、门前或背景不变的地方。我们提出了一种基于相关性的人脸检测算法,在这种环境下检测人脸,我们控制位置,不控制灯光、姿势和比例。结果表明,该算法训练简单、速度快,优于维奥拉和琼斯人脸检测精度,测试速度快。

URL

https://arxiv.org/abs/1903.08649

PDF

https://arxiv.org/pdf/1903.08649.pdf


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