Background subtraction in people detection framework for RGB-D cameras

In this paper, we propose a background subtraction algorithm specific for depth videos from RGB-D cameras. Embedded in a people detection framework, it does not classify foreground / background at pixel level but provides useful information for the framework to remove noise. Noise is only removed wh...

Full description

Saved in:
Bibliographic Details
Published in2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) pp. 241 - 246
Main Authors Anh-Tuan Nghiem, Bremond, Francois
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2014
Subjects
Cameras
Classification algorithms
Equations
Libraries
Noise
Noise measurement
Object tracking
Online AccessGet full text

Cover

More Information
Summary:In this paper, we propose a background subtraction algorithm specific for depth videos from RGB-D cameras. Embedded in a people detection framework, it does not classify foreground / background at pixel level but provides useful information for the framework to remove noise. Noise is only removed when the framework has all the information from background subtraction, classification and object tracking. In our experiment, our background subtraction algorithm outperforms GMM, a popular background subtraction algorithm, in detecting people and removing noise.
DOI:10.1109/AVSS.2014.6918675