Partial Face Detection for Continuous Authentication

TL;DR

This paper introduces a real-time, part-based face detection method tailored for mobile devices, effectively handling partial and occluded faces for continuous authentication, outperforming existing methods in accuracy and speed.

Contribution

A novel part-based face detection technique optimized for mobile devices that improves detection accuracy and speed for partial and occluded faces.

Findings

Outperforms state-of-the-art face detection methods in accuracy

Achieves faster processing speeds on mobile devices

Effective in detecting partially cropped and occluded faces

Abstract

In this paper, a part-based technique for real time detection of users' faces on mobile devices is proposed. This method is specifically designed for detecting partially cropped and occluded faces captured using a smartphone's front-facing camera for continuous authentication. The key idea is to detect facial segments in the frame and cluster the results to obtain the region which is most likely to contain a face. Extensive experimentation on a mobile dataset of 50 users shows that our method performs better than many state-of-the-art face detection methods in terms of accuracy and processing speed.