Detection of human faces in visual scenes

S. Karungaru, M. Fukumi, N. Akamatsu
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引用次数: 16

Abstract

This paper presents a neural network based high-speed system to detect faces in any visual scene. This paper proposes a high-speed and accurate method to search for human faces using a "Knowledge" pruned small sized neural network, and skin colour detection using threshold method with confirmation by a skin colour detection neural network (TSCD). This project is made up of two parts: the face detecting system (FDS) and the TSCD. The FDS that is used to detect faces is made up of a knowledge pruned face locator, a down sampler, and a merger. The TSCD does a high-speed reduction of the face search area to skin regions (and then to face candidates). The TSCD assumes, correctly, that a human face (without wearing any mask or painting) in a visual scene can only be found in a skin colour region. However, all skin regions containing faces must be found otherwise the overall system accuracy goes down.
视觉场景中人脸的检测
提出了一种基于神经网络的高速人脸检测系统。本文提出了一种基于“知识”修剪的小型神经网络的快速、准确的人脸搜索方法,以及基于肤色检测神经网络(TSCD)确认的阈值法的肤色检测方法。本课题由两部分组成:人脸检测系统(FDS)和TSCD。用于人脸检测的FDS由一个知识剪枝人脸定位器、一个down采样器和一个合并器组成。TSCD将人脸搜索区域高速缩小到皮肤区域(然后再缩小到人脸候选区域)。TSCD正确地假设,在视觉场景中,人脸(没有戴任何面具或绘画)只能在肤色区域中找到。但是,必须找到包含人脸的所有皮肤区域,否则整个系统的准确性将下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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