  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.
