Deep feature-based face detection on mobile devices

Sayantan Sarkar, Vishal M. Patel, R. Chellappa
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引用次数: 38

Abstract

We propose a deep feature-based face detector for mobile devices to detect user's face acquired by the front-facing camera. The proposed method is able to detect faces in images containing extreme pose and illumination variations as well as partial faces. The main challenge in developing deep feature-based algorithms for mobile devices is the constrained nature of the mobile platform and the non-availability of CUDA enabled GPUs on such devices. Our implementation takes into account the special nature of the images captured by the front-facing camera of mobile devices and exploits the GPUs present in mobile devices without CUDA-based frameworks, to meet these challenges.
移动设备上基于深度特征的人脸检测
我们提出了一种基于深度特征的移动设备人脸检测器,用于检测前置摄像头获取的用户人脸。所提出的方法能够检测包含极端姿态和光照变化的图像中的人脸以及部分人脸。为移动设备开发基于深度特征的算法的主要挑战是移动平台的约束性质以及此类设备上支持CUDA的gpu的不可用性。我们的实现考虑到移动设备前置摄像头捕获的图像的特殊性,并利用移动设备中没有基于cuda框架的gpu来应对这些挑战。
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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