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Gool, L.: Real-time facial feature detection using conditional regression forests (2012)
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@MISC{Dantone12gool,l.:,
author = {Matthias Dantone and Juergen Gall and Gabriele Fanelli Luc Van Gool},
title = {Gool, L.: Real-time facial feature detection using conditional regression forests},
year = {2012}
}
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Abstract
Although facial feature detection from 2D images is a well-studied field, there is a lack of real-time methods that estimate feature points even on low quality images. Here we propose conditional regression forest for this task. While regression forest learn the relations between facial image patches and the location of feature points from the entire set of faces, conditional regression forest learn the relations conditional to global face properties. In our experiments, we use the head pose as a global property and demonstrate that conditional regression forests outperform regression forests for facial feature detection. We have evaluated the method on the challenging Labeled Faces in the Wild [20] database where close-to-human accuracy is achieved while processing images in real-time. 1.
Keyphrases
conditional regression forest real-time facial feature detection feature point regression forest facial feature detection head pose conditional regression close-to-human accuracy global face property real-time method global property facial image patch well-studied field low quality image entire set
