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A Robust Geometric Skin Colour Face Detection Method under Unconstrained Environment of Smartphone Database

机译:智能手机数据库无约束环境下的鲁棒几何肤色人脸检测方法

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摘要

Face detection is the primary task in building a vision-based human-computer interaction system and in special applications such as face recognition, face tracking, face identification, expression recognition and also content-based image retrieval. A potent face detection system must be able to detect faces irrespective of illuminations, shadows, cluttered backgrounds, orientation and facial expressions. In previous literature, many approaches for face detection had been proposed. However, face detection in outdoor images with uncontrolled illumination and images with complex background are still a serious problem. Hence, in this paper, we had proposed a Geometric Skin Colour (GSC) method for detecting faces accurately in real world image, under capturing conditions of both indoor and outdoor, and with a variety of illuminations and also in cluttered backgrounds. The selected method was evaluated on two different face video smartphone databases and the obtained results proved the outperformance of the proposed method under the unconstrained environment of these databases.
机译:人脸检测是构建基于视觉的人机交互系统以及特殊应用(例如人脸识别,人脸跟踪,人脸识别,表情识别以及基于内容的图像检索)的主要任务。一个有效的面部检测系统必须能够检测面部,而与光照,阴影,背景混乱,方向和面部表情无关。在先前的文献中,已经提出了许多用于面部检测的方法。然而,在具有不受控制的照明的室外图像和具有复杂背景的图像中的面部检测仍然是一个严重的问题。因此,在本文中,我们提出了一种几何肤色法(GSC),该方法可以在室内和室外,各种照明条件下以及杂乱背景下,在真实世界的图像中准确检测人脸。在两个不同的人脸视频智能手机数据库上对所选方法进行了评估,所得结果证明了该方法在这些数据库不受限制的环境下的性能。

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