Brilakis, I and Zhu, Z and German, S (2011) Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure. In: the 2011 NSF Engineering Research and Innovation Conference, 2011-1-4 to 2011-1-7, Atlanta, GA, United States of America.Full text not available from this repository.
As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
|Divisions:||Div D > Construction Engineering|
|Depositing User:||Cron Job|
|Date Deposited:||09 Dec 2016 18:40|
|Last Modified:||25 Feb 2017 01:21|