Automatic face recognition for home safety using video-based side-view face images

Automatic face recognition for home safety using video-based side-view face images

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Biometrics — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Face recognition from side-view positions is an essential task for recognition systems with real-world scenarios. Most of the existing face recognition methods rely on alignment of face images into some canonical form. However, alignment in side-view faces can be challenging due to lack of symmetry and a small number of reliable reference points. To the best of the author's knowledge, only a few of the existing methods deal with video-based face recognition from side-view images, and not many databases include sufficient video footage to study this task. Here, the authors propose an automatic side-view face recognition system designed for home safety applications. They first contribute a newly collected video face database, named UT-DOOR, where 98 subjects were recorded with four cameras attached at doorposts as they pass through doors. Secondly, they propose a face recognition system, where they automatically detect and recognise faces using side-view images in videos. One of the attractive properties of this system is that they use cameras with limited view angle to preserve the privacy of the people. They review several databases and test their system both on the CMU Multi-PIE database and the UT-DOOR database for comparison. Experimental results show that their system can successfully recognise side-view faces from videos.

Related content

This is a required field
Please enter a valid email address