Pole-shaped objects (PSOs) located along a road play key role in road safety and planning. Automation is required for calculating the numbers of trees need to be removed and utility poles need to be relocated during rural road widening. Road-side poles are among the most frequently struck road-side objects during road-side accidents. An automatic method is therefore proposed for detecting PSOs using LiDAR point cloud captured along the roadway using Mobile LiDAR system. The proposed method is tested on the point cloud data of rural road environment in India. Dataset of study area having text file size of 1.22 GB is processed in 13 minutes resulting in completeness of 88.63 % and correctness of 95.12 % in identifying PSOs within 10m of the r...
Mobile LiDAR captures complete details of street trees located along roadway and it is most efficien...
This study aims at building a robust semi-automated pavement marking extraction workflow based on th...
Conference Name:5th International Conference on Geo-Information Technologies for Natural Disaster Ma...
Mobile Laser Scanning (MLS) point cloud data contains rich three-dimensional (3D) information on roa...
The accurate three-dimensional road surface information is highly useful for health assessment and m...
AbstractThis paper presents novel approach for detection of pole-like objects from LIDAR data. The d...
The digital mapping of road environment is an important task for road infrastructure inventory and u...
The United Nations (UN) stated that all new roads and 75% of travel time on roads must be 3+ star st...
Due to the road safety problem is becoming more and more serious recent years, existing road safety ...
Due to the road safety problem is becoming more and more serious recent years, existing road safety ...
Dense point clouds can be collected efficiently from large areas using mobile laser scanning (MLS) t...
Dense point clouds can be collected efficiently from large areas using mobile laser scanning (MLS) t...
Abstract: Accurate road environment information is needed in applications such as road maintenance a...
This study presents a method for automatic extraction of road lane markings from mobile light detect...
Road damage detection is important for road safety and road maintenance planning. Road surface anoma...
Mobile LiDAR captures complete details of street trees located along roadway and it is most efficien...
This study aims at building a robust semi-automated pavement marking extraction workflow based on th...
Conference Name:5th International Conference on Geo-Information Technologies for Natural Disaster Ma...
Mobile Laser Scanning (MLS) point cloud data contains rich three-dimensional (3D) information on roa...
The accurate three-dimensional road surface information is highly useful for health assessment and m...
AbstractThis paper presents novel approach for detection of pole-like objects from LIDAR data. The d...
The digital mapping of road environment is an important task for road infrastructure inventory and u...
The United Nations (UN) stated that all new roads and 75% of travel time on roads must be 3+ star st...
Due to the road safety problem is becoming more and more serious recent years, existing road safety ...
Due to the road safety problem is becoming more and more serious recent years, existing road safety ...
Dense point clouds can be collected efficiently from large areas using mobile laser scanning (MLS) t...
Dense point clouds can be collected efficiently from large areas using mobile laser scanning (MLS) t...
Abstract: Accurate road environment information is needed in applications such as road maintenance a...
This study presents a method for automatic extraction of road lane markings from mobile light detect...
Road damage detection is important for road safety and road maintenance planning. Road surface anoma...
Mobile LiDAR captures complete details of street trees located along roadway and it is most efficien...
This study aims at building a robust semi-automated pavement marking extraction workflow based on th...
Conference Name:5th International Conference on Geo-Information Technologies for Natural Disaster Ma...