@InProceedings{AlbertClapes2012,
author="Albert Clapes
and Miguel Reyes
and Sergio Escalera",
title="User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis",
booktitle="7th Conference on Articulated Motion and Deformable Objects",
year="2012",
publisher="Springer Berlin Heidelberg",
volume="7378",
pages="1--11",
abstract="We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches.",
optnote="HUPBA;MILAB",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2010), last updated on Thu, 18 Jan 2018 11:42:50 +0100",
isbn="978-3-642-31566-4",
issn="0302-9743",
doi="10.1007/978-3-642-31567-1_1",
file=":http://refbase.cvc.uab.es/files/CRE2012.pdf:PDF"
}