Deep Feature-based Face Detection on Mobile Devices

TL;DR

This paper introduces a deep feature-based face detection method optimized for mobile devices, capable of handling extreme poses, lighting, and partial faces by leveraging mobile GPU capabilities without CUDA.

Contribution

It presents a novel face detection approach tailored for mobile platforms that overcomes hardware constraints and diverse image conditions.

Findings

Effective detection in extreme pose and illumination conditions

Utilizes mobile GPU resources without CUDA frameworks

Achieves real-time performance on mobile devices

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 frameorks, to meet these challenges.