How Far Can You Get By Combining Change Detection Algorithms?
May 12, 2015 Β· Declared Dead Β· π International Conference on Image Analysis and Processing
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Authors
Simone Bianco, Gianluigi Ciocca, Raimondo Schettini
arXiv ID
1505.02921
Category
cs.CV: Computer Vision
Citations
121
Venue
International Conference on Image Analysis and Processing
Last Checked
4 months ago
Abstract
Given the existence of many change detection algorithms, each with its own peculiarities and strengths, we propose a combination strategy, that we termed IUTIS (In Unity There Is Strength), based on a genetic Programming framework. This combination strategy is aimed at leveraging the strengths of the algorithms and compensate for their weakness. In this paper we show our findings in applying the proposed strategy in two different scenarios. The first scenario is purely performance-based. The second scenario performance and efficiency must be balanced. Results demonstrate that starting from simple algorithms we can achieve comparable results with respect to more complex state-of-the-art change detection algorithms, while keeping the computational complexity affordable for real-time applications.
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