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Computer vision based traffic analysis for real-time traffic density estimation
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blr246/traffic
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Copyright 2011-2012 Brandon L. Reiss This software package contains implementations of two vehicle density estimators designed for daytime and nighttime traffic density estimation. The daytime estimator uses a Gaussian Mixture Model background subtraction technique in order to label candidate pixels that correspond the vehicular traffic. The nighttime technique uses a simple median filtering, averaging, and morpholocial operations to perform bright object detection in a nighttime sequence of traffic images. Both methods demonstrate potential to characterize traffic density by the correlation of their output signals to the obeserved traffic density in some image sequences. The nighttime algorithm is more robust mostly due to the reduced complexity of the problem of finding bright headlights in a mostly dark image. The author of the software is Brandon L. Reiss, and he can be reached at [email protected]. All uses of the software are subject to the license agreement prepended to each source file. A copy of the license is also included inside the file called LICENSE.
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