Most of the automated video-surveillance applications are based on background (BG) subtraction techniques, that aim at distinguishing moving objects in a static scene. These strategies strongly depend on the BG model, that has to be initialized and updated. A good initialization is crucial for the successive processing. In this paper, we propose a novel method for BG initialization and recovery, that merges interesting ideas coming from the video inpainting and the generative modelling subfields. The method takes as input a video sequence, in which several objects move in front of a stationary BG. Then, a statistical representation of the BG is iteratively built, discarding the moving objects in a fully automatic way. The method is based on the following hypotheses: (i) a portion of the BG, called sure BG, can be identified with high certainty by using only per-pixel reasoning and (ii) the remaining scene BG can be generated utilizing exemplars of the sure BG. The proposed algorithm is able to exploit these hypotheses in a principled and effective way.

Exemplar-based Background Model lnitialization

COLOMBARI, ANDREA;CRISTANI, Marco;MURINO, Vittorio;FUSIELLO, Andrea
2005-01-01

Abstract

Most of the automated video-surveillance applications are based on background (BG) subtraction techniques, that aim at distinguishing moving objects in a static scene. These strategies strongly depend on the BG model, that has to be initialized and updated. A good initialization is crucial for the successive processing. In this paper, we propose a novel method for BG initialization and recovery, that merges interesting ideas coming from the video inpainting and the generative modelling subfields. The method takes as input a video sequence, in which several objects move in front of a stationary BG. Then, a statistical representation of the BG is iteratively built, discarding the moving objects in a fully automatic way. The method is based on the following hypotheses: (i) a portion of the BG, called sure BG, can be identified with high certainty by using only per-pixel reasoning and (ii) the remaining scene BG can be generated utilizing exemplars of the sure BG. The proposed algorithm is able to exploit these hypotheses in a principled and effective way.
2005
1595932429
Video surveillance; background initialization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/27070
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