Fast Moving Objects Detection Using iLBP Background Model

B. V. Vishnyakov, Vladimir S. Gorbatsevich, Sergey V. Sidyakin, Yu. V. Vizilter, Ivan K. Malin, А. И. Егоров · ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · 2014

Abstract. In this paper a new approach for moving objects detection in video surveillance systems is proposed. It is based on iLBP (intensity local binary patterns) descriptor that combines the classic LBP (local binary patterns) and the multiple regressive pseudospectra model. The iLBP descriptor itself is considered together with computational algorithm that is based on the sign image representation. We show that motion analysis methods based on iLBP allow uniformly detecting objects that move with different speed or even stop for a short while along with unattended objects. We also show that proposed model is comparable to the most popular modern background models, but is significantly faster.

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