@InProceedings{AntonioHernandez2010,
author="Antonio Hernandez
and Miguel Reyes
and Sergio Escalera
and Petia Radeva",
title="Spatio-Temporal GrabCut human segmentation for face and pose recovery",
booktitle="IEEE International Workshop on Analysis and Modeling of Faces and Gestures",
year="2010",
pages="33--40",
abstract="In this paper, we present a full-automatic Spatio-Temporal GrabCut human segmentation methodology. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model for seed initialization. Spatial information is included by means of Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, human segmentation is combined with Shape and Active Appearance Models to perform full face and pose recovery. Results over public data sets as well as proper human action base show a robust segmentation and recovery of both face and pose using the presented methodology.",
optnote="MILAB;HUPBA",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1362), last updated on Thu, 18 Jan 2018 11:59:20 +0100",
isbn="978-1-4244-7029-7",
issn="2160-7508",
doi="10.1109/CVPRW.2010.5543824"
}