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

• Published in: Machine vision and applications 2014-08, Vol.25 (6), p.1573-1584
• Main Authors: Romanoni, Andrea, Matteucci, Matteo, Sorrenti, Domenico G.
• Format: Article
• Language: English
• Subjects: Algorithms; Applied sciences; Artificial intelligence; Cameras; Classification; Communications Engineering; Computer Science; Computer science; control theory; systems; Errors; Exact sciences and technology; Histograms; Image Processing and Computer Vision; Movement; Networks; Original Paper; Pattern Recognition; Pattern recognition. Digital image processing. Computational geometry; Pixels; Subtraction; Temporal logic; Translations; Vibration; Vision systems
• ISSN: 0932-8092; 1432-1769
• DOI: 10.1007/s00138-013-0587-9

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.