Machine Vision and Applications

, Volume 25, Issue 6, pp 1573–1584 | Cite as

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

  • Andrea Romanoni
  • Matteo Matteucci
  • Domenico G. Sorrenti
Original Paper


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.


Background subtraction Moving camera Temporal background subtraction Spatio-Temporal background subtraction 



This work has been supported by SMELLER (Sistema di monitoraggio delle emissioni di singoli veicoli in tempo reale, Real Time Monitoring System of the Exhaust Emission of Individual Vehicles), a project funded by Regione Lombardia, Italy.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andrea Romanoni
    • 1
  • Matteo Matteucci
    • 1
  • Domenico G. Sorrenti
    • 2
  1. 1.Politecnico di Milano, DEIBMilanItaly
  2. 2.Universitá degli Studi Milano-Bicocca, DISCoMilanItaly

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