Abstract
Pole-Like Objects (PLOs) situated along the corridor of street environment are critical roadway resources. They play major role in road safety inspection and road planning. Road side poles need to be relocated during rural and urban road widening. Road side objects including pole, street trees are among the most commonly struck road-side objects during road-side accidents. Use of Terrestrial Laser Scanning (TLS) technology for mapping of road side objects is a critical revolution in case of field surveying. Automatic detection of road side objects help in maintaining and managing of road surface. In present study a novel five-step method is proposed to detect PLOs along the roadway using TLS data. The first step, i.e. clustering of data, uses the K-means clustering method in order to divide the data into smaller chunks. Further, ground filtering is performed at each cluster of data in next step. Two dimensional projection and range search is used to extract the proximity points of selected seed point. In last step Analytical Hierarchy Process (AHP) is used to detect the PLOs. The proposed method is tested on a captured TLS point cloud data. Correctness and completeness, respectively of 98.18% and 96.42%, are achieved.
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Husain, A., Vaishya, R.C. (2018). An AHP Based Automated Approach for Pole-like Objects Detection Using Three Dimensional Terrestrial Laser Scanner Data. In: Bhattacharyya, P., Sastry, H., Marriboyina, V., Sharma, R. (eds) Smart and Innovative Trends in Next Generation Computing Technologies. NGCT 2017. Communications in Computer and Information Science, vol 828. Springer, Singapore. https://doi.org/10.1007/978-981-10-8660-1_52
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DOI: https://doi.org/10.1007/978-981-10-8660-1_52
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