Information based multimodal Background Subtraction for Traffic Monitoring Applications
Translated title
Author
Term
4. term
Publication year
2015
Submitted on
2015-06-01
Pages
102
Abstract
This thesis presents a new approach to background subtraction for multimodal systems. The work is an extension to the Gaussian mixture model background subtraction of Stauffer and Grimson. The background conformity values of two image sources, namely thermal and RGB, are fused in order to enable stable background subtraction for persistent surveillance. Image quality heuristics based on image characteristics and external sources are specified to evaluate the usefulness of the modalities and perform the fusion context aware. Extensions for the use of the system for the purpose of traffic monitoring are presented. Therefor modulations of a new image representation of the conformity of pixels with the background model are made. The potential of the proposed method has been shown during excessive tests of quantitative and qualitative characteristics.
Keywords
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