Abstract
An application-oriented vision-based traffic scene sensor system is designed. Its most important vision modules are identified and their algorithms are described in details: the on-line auto-calibration modules and three optional modules for 2-D measurement tasks (i.e. queue length detection, license plate identification and vehicle classification). It is shown that all three tasks may be regarded as applications of an iconic image classification scheme. Such a general scheme is developed and it can be applied for the above mentioned tasks by exchanging the application-dependent modules for pre-segmentation and feature extraction. The practical background of described work constitutes the IST project OMNI, dealing with the development of a network-wide intersection-driven model that can take advantage from the existence of advanced sensors, i.e. video sensors and vehicles equipped with GPS/GSM.
This work was supported by the EC project IST-11250: “Open Model For Network-Wide Heterogeneous Intersection-Based Transport Management (OMNI)”.
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Kasprzak, W. (2001). An Iconic Classification Scheme for Video-Based Traffic Sensor Tasks. In: Skarbek, W. (eds) Computer Analysis of Images and Patterns. CAIP 2001. Lecture Notes in Computer Science, vol 2124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44692-3_87
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DOI: https://doi.org/10.1007/3-540-44692-3_87
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