Mobile Laser Scanned Point Clouds for Road Object Detection and Extraction: A Review
The mobile laser scanning (MLS) technique has attracted considerable attention for providing high density, high accuracy, unstructured, three dimensional (3D) geo referenced point cloud coverage of the road environment. Recently, there has been an increasing number of applications of MLS in the detection and extraction of urban objects. This paper presents a systematic review of existing MLS related literature. This paper consists of three parts. Part 1 presents a brief overview of the state of the art commercial MLS systems. Part 2 provides a detailed analysis of on road and off road information inventory methods, including the detection and extraction of on road objects (e.g. road surface, road markings, driving lines, and road crack) and off road objects (e.g. pole like objects and power lines) Part 3 presents a refined integrated analysis of challenges and future trends. Our review shows that MLS technology is well proven in urban object detection and extraction, since the improvement of hardware and software accelerate the efficiency and accuracy of data collection and processing. When compared to other review papers focusing on MLS applications, we review the state of the art road object detection and extraction methods using MLS data and discuss their performance and applicability. The main contribution of this review demonstrates that the MLS systems are suitable for supporting road asset inventory, ITS related applications, high definition maps, and other highly accurate localization services.
Remote. Sens.