Detecting low-resolution faces in video

Neil Robertson, Nils Janssen

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a method for the detection of faces (via skin regions) in images where faces may be low-resolution and no assumptions are made about fine facial features being visible. This type of data is challenging because changes in appearance of skin regions occur due to changes in both lighting and resolution. We present a non-parametric classification scheme based on a histogram similarity measure. By comparing performance of commonly-used colour-spaces we find that the YIQ colour space with 16 histogram bins (in both 1 and 2 dimensions) gives the most accurate performance over a wide range of imaging conditions for non-parametric skin classification. We demonstrate better performance of the non-parametric approach vs. colour thresholding and a Gaussian classifier. Face detection is subsequently achieved via a simple aspect-ratio and we show results from indoor and outdoor scenes. © 2009 SPIE-IS&T.

Original languageEnglish
Article number725207
JournalProceedings of SPIE - the International Society for Optical Engineering
Volume7252
DOIs
Publication statusPublished - 2009
EventIntelligent Robots and Computer Vision XXVI: Algorithms and Techniques - San Jose, CA, United States
Duration: 19 Jan 200920 Jan 2009

Fingerprint Dive into the research topics of 'Detecting low-resolution faces in video'. Together they form a unique fingerprint.

Cite this