REAL-TIME MOVING OBJECT DETECTION IN VIDEO SEQUENCES USING SPATIO-TEMPORAL ADAPTIVE GAUSSIAN MIXTURE MODELS

Katharina Quast, Matthias Obermann, André Kaup

2010

Abstract

In this paper we present a background subtraction method for moving object detection based on Gaussian mixture models which performs in real-time. Our method improves the traditional Gaussian mixture model (GMM) technique in several ways. It takes into account spatial and temporal dependencies, as well as a limitation of the standard deviation leading to a faster update of the model and a smoother object mask. A shadow detection method which is able to remove the umbra as well as the penumbra in one single processing step is further used to get a mask that fits the object outline even better. Using the computational power of parallel computing we further speed up the object detection process.

Paper Citation

in Harvard Style

Quast K., Obermann M. and Kaup A. (2010). REAL-TIME MOVING OBJECT DETECTION IN VIDEO SEQUENCES USING SPATIO-TEMPORAL ADAPTIVE GAUSSIAN MIXTURE MODELS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-028-3, pages 413-418. DOI: 10.5220/0002816904130418

in Bibtex Style

@conference{visapp10,
author={Katharina Quast and Matthias Obermann and André Kaup},
title={REAL-TIME MOVING OBJECT DETECTION IN VIDEO SEQUENCES USING SPATIO-TEMPORAL ADAPTIVE GAUSSIAN MIXTURE MODELS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={413-418},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002816904130418},
isbn={978-989-674-028-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)
TI - REAL-TIME MOVING OBJECT DETECTION IN VIDEO SEQUENCES USING SPATIO-TEMPORAL ADAPTIVE GAUSSIAN MIXTURE MODELS
SN - 978-989-674-028-3
AU - Quast K.
AU - Obermann M.
AU - Kaup A.
PY - 2010
SP - 413
EP - 418
DO - 10.5220/0002816904130418