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Robust Curved Road Boundary Identification Using Hierarchical Clustering (2013)
BibTeX
@MISC{Parvin13robustcurved,
author = {Nurjahan Parvin and Nurjahan Parvin},
title = {Robust Curved Road Boundary Identification Using Hierarchical Clustering},
year = {2013}
}
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Abstract
We develop a new method for automatic curved road boundary detection in images captured by traffic cameras. The proposed method combines data driven (edge segments) and model based (2nd degree polynomial models for road boundaries) techniques to identify dominant road boundary in images exhibiting extreme weather conditions, low visibility and poor lighting. The proposed method constructs a ranked list of possible road boundaries through agglomerative hierarchical clustering of edge segments. Each node in the hierarchical clustering is a potential road boundary. Top ranked road boundaries are paired with each other to identify potential road regions. The road regions are then ranked using appearance and perspective cues and the top ranked road region is used to construct the dominant road boundary in the image. We evaluate our method on a realistic dataset captured by traffic cameras managed by Ontario’s Ministry of Transportation. ii Acknowledgements I would like to express my sincere gratitude to my supervisors, Dr. Ken Q. Pu and Dr. Faisal Z. Qureshi for their continuous guidance, support, motivation, and patience during my graduate studies. Special thanks to my fellow lab members, Mohamed Helala, Luis Zarrabeita, Zheng
Keyphrases
dominant road boundary road boundary traffic camera road region edge segment continuous guidance new method extreme weather condition low visibility polynomial model sincere gratitude possible road boundary luis zarrabeita fellow lab member potential road region hierarchical clustering graduate study potential road boundary method combine data mohamed helala agglomerative hierarchical clustering ii acknowledgement realistic dataset special thanks perspective cue poor lighting road boundary detection ranked list ontario ministry
