Deep Feature-based Face Detection on Mobile Devices
This addresses the problem of efficient face detection for mobile users, but it is incremental as it adapts existing deep feature methods to mobile constraints.
The paper tackles face detection on mobile devices under challenging conditions like extreme pose and illumination variations, achieving detection of partial faces by exploiting mobile GPUs without CUDA frameworks.
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.