# Partial Face Detection for Continuous Authentication

arXiv: https://arxiv.org/abs/1603.09364 · HTML: https://mlsanity.com/paper/1603.09364/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Mar 2016.

## Built on by (most cited first, 3 of 3)

- [Attention-based Partial Face Recognition](https://mlsanity.com/paper/2106.06415/) (2021)
- [Towards robustness under occlusion for face recognition](https://mlsanity.com/paper/2109.09083/) (2021)
- [Deep learning for identification and face, gender, expression recognition under constraints](https://mlsanity.com/paper/2111.01930/) (2021)

## Abstract (arXiv)

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.