Koch, C and Brilakis, I (2011) Improving Pothole Recognition through Vision Tracking for Automated Pavement Assessment. In: the 18th EG-ICE Workshop on Intelligent Computing in Engineering, 2011-7-6 to 2011-7-8, Twente, Netherlands pp. 1-8..Full text not available from this repository.
Pavement condition assessment is essential when developing road network maintenance programs. In practice, pavement sensing is to a large extent automated when regarding highway networks. Municipal roads, however, are predominantly surveyed manually due to the limited amount of expensive inspection vehicles. As part of a research project that proposes an omnipresent passenger vehicle network for comprehensive and cheap condition surveying of municipal road networks this paper deals with pothole recognition. Existing methods either rely on expensive and high-maintenance range sensors, or make use of acceleration data, which can only provide preliminary and rough condition surveys. In our previous work we created a pothole detection method for pavement images. In this paper we present an improved recognition method for pavement videos that incrementally updates the texture signature for intact pavement regions and uses vision tracking to track detected potholes. The method is tested and results demonstrate its reasonable efficiency.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
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|Date Deposited:||16 Jul 2015 14:32|
|Last Modified:||26 Jul 2015 01:23|