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Machine Vision and Applications

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01-08-2014 | Original Paper

Background subtraction by combining Temporal and Spatio-Temporal histograms in the presence of camera movement

Authors: Andrea Romanoni, Matteo Matteucci, Domenico G. Sorrenti

Published in: Machine Vision and Applications | Issue 6/2014

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Abstract

Background subtraction is the classical approach to differentiate moving objects in a scene from the static background when the camera is fixed. If the fixed camera assumption does not hold, a frame registration step is followed by the background subtraction. However, this registration step cannot perfectly compensate camera motion, thus errors like translations of pixels from their true registered position occur. In this paper, we overcome these errors with a simple, but effective background subtraction algorithm that combines Temporal and Spatio-Temporal approaches. The former models the temporal intensity distribution of each individual pixel. The latter classifies foreground and background pixels, taking into account the intensity distribution of each pixels’ neighborhood. The experimental results show that our algorithm outperforms the state-of-the-art systems in the presence of jitter, in spite of its simplicity.

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Title: Background subtraction by combining Temporal and Spatio-Temporal histograms in the presence of camera movement
Authors: Andrea Romanoni
Matteo Matteucci
Domenico G. Sorrenti
Publication date: 01-08-2014
Publisher: Springer Berlin Heidelberg
Published in: Machine Vision and Applications / Issue 6/2014
Print ISSN: 0932-8092
Electronic ISSN: 1432-1769
DOI: https://doi.org/10.1007/s00138-013-0587-9

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