ViBe: A Universal Background Subtraction Algorithm for Video Sequences

This paper presents a technique for motion detection that incorporates several innovative mechanisms. For example, our proposed technique stores, for each pixel, a set of values taken in the past at the same location or in the neighborhood. It then compares this set to the current pixel value in ord...

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Vydané v:	IEEE transactions on image processing Ročník 20; číslo 6; s. 1709 - 1724
Hlavní autori:	Barnich, O, Van Droogenbroeck, M
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY IEEE 01.06.2011 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation model Algorithm Algorithms Applied sciences Artificial Intelligence Background Background model Background subtraction Benchmarking C code C/C++ Code Comparision Computation Computational modeling Computer science; control theory; systems Computer vision Detection, estimation, filtering, equalization, prediction Electrical & electronics engineering Embedded systems Engineering, computing & technology Estimation Exact sciences and technology Exponential filtering Fast algorithm Foreground Ghost Image color analysis Image Enhancement - methods Image Interpretation, Computer-Assisted - methods image motion analysis Image processing image segmentation Information, signal and communications theory Ingénierie électrique & électronique Ingénierie, informatique & technologie Initialization Kernel density estimation Learning learning (artificial intelligence) Lighting Mathematical models Mixture of Gaussians Motion Motion analysis Motion detection OpenCV Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Pixel Pixel classification Pixels Pseudo-code Random sampling Real-time processing real-time systems Reproducibility of Results Segmentation Sensitivity and Specificity Signal and communications theory Signal processing Signal Processing, Computer-Assisted Signal representation. Spectral analysis Signal, noise Smart camera State of the art Stores Studies Subtraction Subtraction Technique Subtraction techniques surveillance Telecommunications and information theory ViBe Video processing Video Recording - methods video signal processing vision and scene understanding Performance evaluation State of the art Image processing Video signal Video signal processing Learning Credal approach Image sequence vision and scene understanding pixel classification Motion detection surveillance Localization learning (artificial intelligence) Monitoring Computer vision Background Background subtraction Algorithm Real time system Image motion analysis Image segmentation real-time systems Signal processing Artificial intelligence
ISSN:	1057-7149, 1941-0042, 1941-0042
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Popis
Shrnutí:	This paper presents a technique for motion detection that incorporates several innovative mechanisms. For example, our proposed technique stores, for each pixel, a set of values taken in the past at the same location or in the neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the background model. This approach differs from those based upon the classical belief that the oldest values should be replaced first. Finally, when the pixel is found to be part of the background, its value is propagated into the background model of a neighboring pixel. We describe our method in full details (including pseudo-code and the parameter values used) and compare it to other background subtraction techniques. Efficiency figures show that our method outperforms recent and proven state-of-the-art methods in terms of both computation speed and detection rate. We also analyze the performance of a downscaled version of our algorithm to the absolute minimum of one comparison and one byte of memory per pixel. It appears that even such a simplified version of our algorithm performs better than mainstream techniques.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 scopus-id:2-s2.0-79957497122
ISSN:	1057-7149 1941-0042 1941-0042
DOI:	10.1109/TIP.2010.2101613