Objects detection and tracking in highly congested traffic using compressed video sequences

Authors:
Marcin Bernaś
Affiliations:
Faculty of Transport, Silesian University of Technology, Katowice, Poland
Venue:
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Year:
2012

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Abstract

The paper presents a model to detect and track vehicles in highly congested traffic using low quality (usually compressed) video sequences. Robustness of the model is provided by applying a data fusion for various detection and tracking algorithms. The surveys to find reliable detection algorithms were performed. Basing on the experiments, the model calibration and results were presented. The proposed model provides data, which can be used by traffic engineers in various microscopic traffic simulations.