Independent multimodal background subtraction

Abstract

Background subtraction is a common method for detecting moving objects from static cameras able to achieve real-time performance. However, it is highly dependent on a good background model particularly to deal with dynamic scenes. In this paper a novel real-time algorithm for creating a robust and multimodal background model is presented. The proposed approach is based on an on-line clustering algorithm to create the model and on a novel conditional update mechanism that allows for obtaining an accurate foreground mask. A quantitative comparison of the algorithm with several state-of-the-art methods on a well-known benchmark dataset is provided demonstrating the effectiveness of the approach.

DOI: 10.1201/b12753-8

Extracted Key Phrases

11 Figures and Tables

01020201520162017
Citations per Year

Citation Velocity: 6

Averaging 6 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.

Cite this paper

@inproceedings{Bloisi2012IndependentMB, title={Independent multimodal background subtraction}, author={Domenico Daniele Bloisi and Luca Iocchi}, booktitle={CompIMAGE}, year={2012} }