Review of mobile mapping and surveying technologies

Puente, Iván; González-Jorge, H.; Martínez-Sánchez, J.; Arias, Pedro

doi:10.1016/j.measurement.2013.03.006

Cited by 347 publications

(230 citation statements)

References 30 publications

Supporting

Mentioning

205

Contrasting

Unclassified

Order By: Relevance

“…All of these are firmly integrated on a van or another type of vehicle, but there is a clear trend to increase flexibility combining LiDAR with many different additional sensors. A fairly recent compilation of available MLS systems can be found in [4].…”

Section: Introductionmentioning

confidence: 99%

An Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept

et al. 2016

View full text Add to dashboard Cite

Accurate road asphalt extent delineation is needed for road and street planning, road maintenance, and road safety assessment. In this article, a new approach for automatic roadside delineation is developed based on the line clouds concept. The method relies on line cloud grouping from point cloud laser data. Using geometric criteria, the initial 3D LiDAR point data is structured in lines covering the road surface. These lines are then grouped according to a set of quasi-planar restriction rules. Road asphalt edge limits are extracted from the end points of lines belonging to these groups. Finally a two-stage smoothing procedure is applied to correct for edge occlusions and other anomalies. The method was tested on a 2.1 km stretch of road, and the results were checked using a RTK-GNSS measured dataset as ground truth. Correctness and completeness were 99% and 97%, respectively.

show abstract

Section: Introductionmentioning

confidence: 99%

An Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Later on it was extended to satellite imagery [42] and to the combination of close-range photogrammetry and TLS point clouds [43], where 3D monoplotting has become a standard measuring principle. Today, 3D monoplotting is also used in hybrid image-and LiDAR-based mobile mapping environments [7,8,11] allowing image-based monoscopic 3D measurements in combination with co-registered MLS point clouds. However, these hybrid solutions currently cannot guarantee the spatial and temporal coherence of the image and depth information, which would be required for both accurate and robust 3D measurements and which currently can only be provided by stereovision based mobile mapping.…”

Section: Smart Exploitation Of Cloud-based 3d Image Spacesmentioning

confidence: 99%

Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City

Nebiker

Cavegn

Loesch

2015

IJGI

View full text Add to dashboard Cite

Abstract:In this paper, we introduce the concept and an implementation of geospatial 3D image spaces as new type of native urban models. 3D image spaces are based on collections of georeferenced RGB-D imagery. This imagery is typically acquired using multi-view stereo mobile mapping systems capturing dense sequences of street level imagery. Ideally, image depth information is derived using dense image matching. This delivers a very dense depth representation and ensures the spatial and temporal coherence of radiometric and depth data. This results in a high-definition WYSIWYG ("what you see is what you get") urban model, which is intuitive to interpret and easy to interact with, and which provides powerful augmentation and 3D measuring capabilities. Furthermore, we present a scalable cloud-based framework for generating 3D image spaces of entire cities or states and a client architecture for their web-based exploitation. The model and the framework strongly support the smart city notion of efficiently connecting the urban environment and its processes with experts and citizens alike. In the paper we particularly investigate quality aspects of the urban model, namely the obtainable georeferencing accuracy and the quality of the depth map extraction. We show that our image-based georeferencing approach is capable of improving the original direct georeferencing accuracy by an order of magnitude and that the presented new multi-image matching approach is capable of providing high accuracies along with a significantly improved completeness of the depth maps.

show abstract

“…Among the various kinds of digital maps, road maps represented by line segments and spline curves with information such as white lines, road markings, and curbs have recently been drawing attention. The recently developed mobile mapping system (MMS) [5] makes it possible to generate these maps. As examples of works using maps, Schreiber et al [6] proposed a method of vehicle localization based on cross-checking detected line segments against the map.…”

Section: Introductionmentioning

confidence: 99%

Line-Based SLAM Using Non-Overlapping Cameras in an Urban Environment

Kawasaki

Hara

Saitō

2018

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYWe propose a method of line-based Simultaneous Localization and Mapping (SLAM) using non-overlapping multiple cameras for vehicles running in an urban environment. It uses corresponding line segments between images taken by different frames and different cameras. The contribution is a novel line segment matching algorithm by warping processing based on urban structures. This idea significantly improves the accuracy of line segment matching when viewing direction are very different, so that a number of correspondences between front-view and rear-view cameras can be found and the accuracy of SLAM can be improved. Additionally, to enhance the accuracy of SLAM we apply a geometrical constraint of urban area for initial estimation of 3D mapping of line segments and optimization by bundle adjustment. We can further improve the accuracy of SLAM by combining points and lines. The position error is stable within 1.5m for the entire image dataset evaluated in this paper. The estimation accuracy of our method is as high as that of ground truth captured by RTK-GPS. Our high accuracy SLAM algorithm can be apply for generating a road map represented by line segments. According to an evaluation of our generating map, true positive rate around the vehicle exceeding 70% is achieved.

show abstract

Review of mobile mapping and surveying technologies

Cited by 347 publications

References 30 publications

An Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept

An Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept

Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City

Line-Based SLAM Using Non-Overlapping Cameras in an Urban Environment

Contact Info

Product

Resources

About