Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds (original) (raw)

2015, IEEE Transactions on Geoscience and Remote Sensing

The Extraction of Street Curbs from Mobile Laser Scanning Data in Urban Areas

Remote Sensing

The demand for mobile laser scanning in urban areas has grown in recent years. Mobile-based light detection and ranging (LiDAR) technology can be used to collect high-precision digital information on city roads and building façades. However, due to the small size of curbs, the information that can be used for curb detection is limited. Moreover, occlusion may cause the extraction method unable to correctly capture the curb area. This paper presents the development of an algorithm for extracting street curbs from mobile-based LiDAR point cloud data to support city managers in street deformation monitoring and urban street reconstruction. The proposed method extracts curbs in three complex scenarios: vegetation covering the curbs, curved street curbs, and occlusion curbs by vehicles, pedestrians. This paper combined both spatial information and geometric information, using the spatial attributes of the road boundary. It can adapt to different heights and different road boundary struct...

The Method of Road Facility Extraction from LiDAR Point Clouds

Various researches and technologies are being developed and utilized to improve the function of autonomous vehicle. These systems have been developed from simple systems that assisted drivers for safe driving. More recently, an autonomous vehicle, which can be driven without driver with control the steering wheel through the vehicle object recognition, has passed a test driving and is driving on real roads. To travel on the public road, it is necessary to recognize road facilities and have positioning technology, which are the basic technologies for the safe driving of autonomous vehicle. The target facilities to be recognized by autonomous vehicles are medians, curbs, and lanes among facilities that must be recognized for the safe driving of autonomous vehicle. In particular, the recognition of road facilities should be applicable under various conditions to reflect actual driving environments and accuracy at a certain level should be guaranteed. In this study a research is conducted on the mapping of road facilities using Light Detection and Ranging (LiDAR) and the extraction of information of road facilities. Surrounding information was mapped using LiDAR data acquired while driving vehicle, and road facility information was obtained using mapped PointCloud.

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