The Potential of Active Contour Models in Extracting Road Edges from Mobile Laser Scanning Data

Active contour models present a robust segmentation approach, which makes efficient use of specific information about objects in the input data rather than processing all of the data. They have been widely-used in many applications, including image segmentation, object boundary localisation, motion tracking, shape modelling, stereo matching and object reconstruction. In this paper, we investigate the potential of active contour models in extracting road edges from Mobile Laser Scanning (MLS) data. The categorisation of active contours based on their mathematical representation and implementation is discussed in detail. We discuss an integrated version in which active contour models are combined to overcome their limitations. We review various active contour-based methodologies, which have been developed to extract road features from LiDAR and digital imaging datasets. We present a case study in which an integrated version of active contour models is applied to extract road edges from MLS dataset. An accurate extraction of left and right edges from the tested road section validates the use of active contour models. The present study provides valuable insight into the potential of active contours for extracting roads from 3D LiDAR point cloud data

Pavement Surface Evaluation Using Mobile Terrestrial LiDAR Scanning Systems

Periodic measurement of pavement surfaces for pavement management system (PMS) data collection is vital for state transportation agencies. Vehicle-based mobile light detection and ranging (LiDAR) systems can be used as a versatile tool to collect point data throughout a roadway corridor. The overall goal of this research is to investigate if mobile terrestrial LiDAR Scanning (MTLS) systems can be used as an efficient and effective method to create accurate digital pavement surfaces for. LiDAR data were collected by five MTLS vendors. In particular, the research is interested in three things: 1) how accurate MTLS is for collecting roadway cross slopes; 2) what is the potential for using MTLS digital pavement surfaces to do materials calculations for pavement rehabilitation projects; and 3) examine the benefit of using MTLS to identify pavement rutting locations. Cross slopes were measured at 23 test stations using traditional surveying methods (conventional leveling served as ground-truth) and compared with adjusted and unadjusted MTLS extracted cross slopes. The results indicate that both adjusted and unadjusted MTLS derived cross slopes meet suggested cross slope accuracies (±0.2%). Application of unadjusted MTLS instead of post-processed MTLS point clouds may decrease/eliminate the cost of a control surveys. The study also used a novel approach to process the MTLS data in a geographic information system (GIS) environment to create a 3-dimension raster representation of a roadway surface. MTLS data from each vendor was evaluated in terms of the accuracy and precision of their raster surface. The resultant surfaces were compared between vendors and with a raster surface created from a centerline profile and 100-ft. cross-section data obtained using traditional surveying methods. When comparing LiDAR data between compliant MTLS vendors, average raster cell height differences averaged 0.21 inches, indicating LiDAR data has considerable potential for creating accurate pavement material volume estimates. The application of MTLS data was also evaluated in terms of the accuracy of collected transverse profiles. Transverse profiles captured from MTLS systems have been compared to 2-inch interval field data collection using partial curve mapping (PCM), Frechet distance, area, curve length, and Dynamic Time Warping (DTW) techniques. The results indicated that there is potential for MTLS systems for use in creating an accurate transverse profile for potential identification of pavement rut areas. This research also identified a novel approach for determining pavement rut areas based on the shape of grid cells. This rather simplistic approach is easily implementable on a network wide basis depending on MTLS point cloud availability. The method does not require the calculation/estimation of an ideal surface to determine rut depths/locations

Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree

13 p.Safe roads are a necessity for any society because of the high social costs of traffic accidents. This challenge is addressed by a novel methodology that allows us to evaluate road safety from Mobile LiDAR System data, taking advantage of the road alignment due to its influence on the accident rate. Automation is obtained through an inductive reasoning process based on a decision tree that provides a potential risk assessment. To achieve this, a 3D point cloud is classified by an iterative and incremental algorithm based on a 2.5D and 3D Delaunay triangulation, which apply different algorithms sequentially. Next, an automatic extraction process of road horizontal alignment parameters is developed to obtain geometric consistency indexes, based on a joint triple stability criterion. Likewise, this work aims to provide a powerful and effective preventive and/or predictive tool for road safety inspections. The proposed methodology was implemented on three stretches of Spanish roads, each with different traffic conditions that represent the most common road types. The developed methodology was successfully validated through as-built road projects, which were considered as “ground truth.”S

A Classification-Segmentation Framework for the Detection of Individual Trees in Dense MMS Point Cloud Data Acquired in Urban Areas

International audienceIn this paper, we present a novel framework for detecting individual trees in densely sampled 3D point cloud data acquired in urban areas. Given a 3D point cloud, the objective is to assign point-wise labels that are both class-aware and instance-aware, a task that is known as instance-level segmentation. To achieve this, our framework addresses two successive steps. The first step of our framework is given by the use of geometric features for a binary point-wise semantic classification with the objective of assigning semantic class labels to irregularly distributed 3D points, whereby the labels are defined as " tree points " and " other points ". The second step of our framework is given by a semantic segmentation with the objective of separating individual trees within the " tree points ". This is achieved by applying an efficient adaptation of the mean shift algorithm and a subsequent segment-based shape analysis relying on semantic rules to only retain plausible tree segments. We demonstrate the performance of our framework on a publicly available benchmark dataset, which has been acquired with a mobile mapping system in the city of Delft in the Netherlands. This dataset contains 10.13 M labeled 3D points among which 17.6% are labeled as " tree points ". The derived results clearly reveal a semantic classification of high accuracy (up to 90.77%) and an instance-level segmentation of high plausibility, while the simplicity, applicability and efficiency of the involved methods even allow applying the complete framework on a standard laptop computer with a reasonable processing time (less than 2.5 h)

Aspects of Accuracy, Scanning Angle Optimization, and Intensity Calibration Related to Nationwide Laser Scanning

Osajulkaisut: Publication 1: Ahokas, E., Kaartinen, H., Hyyppä, J. 2004. A quality assessment of repeated airborne laser scanner observations. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Istanbul, Turkey, Vol. XXXV, part B3, pp. 237-242. ISSN 1682-1750. Publication 2: Ahokas, E., Hyyppä, J., Kaartinen, H., Kukko, A., Kaasalainen, S., Krooks, A. 2010. The effect of biomass and scanning angle on laser beam transmittance. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vienna, Austria, Vol. XXXVIII(7A), pp. 1-6. ISSN 1682-1777. http://www.isprs.org/proceedings/XXXVIII/part7/a/pdf/1_XXXVIII-part7A.pdf Publication 3: Ahokas, E., Hyyppä, J., Yu, X., Holopainen, M. 2011. Transmittance of Airborne Laser Scanning Pulses for Boreal Forest Elevation Modeling. Remote Sensing. 3, 1365-1379. ISSN 2072-4292. http://www.mdpi.com/2072-4292/3/7/1365/ Publication 4: Kaasalainen, S., Ahokas, E., Hyyppä, J., Suomalainen, J. 2005. Study of surface brightness from backscattered laser intensity: Calibration of laser data. IEEE Geoscience and remote sensing letters, Vol. 2, No. 3, pp. 255-259, ISSN 1545-598X. Publication 5: Ahokas, E., Kaasalainen, S., Hyyppä, J., Suomalainen, J. 2006. Calibration of the Optech ALTM 3100 laser scanner intensity data using brightness targets. ISPRS Commission I Symposium, Paris Marne-la-Vallee, 4-6 July 2006, ISPRS Volume XXXVI Part 1/A. pp. 14-20. CD-ROM publication. Also in Revue Française de Photogrammétrie et de Télédétection, No. 182, (2006-2), pp. 10-16. Publication 6: Honkavaara, E., Peltoniemi J., Ahokas, E., Kuittinen R., Hyyppä, J., Jaakkola, J., Kaartinen, H., Markelin, L., Nurminen, K., Suomalainen, J. 2008. A Permanent Test Field for Digital Photogrammetric Systems. Photogrammetric Engineering and Remote Sensing. Vol. 74, No. 1, pp. 95-106.Airborne laser scanning is a technique that produces three-dimensional coordinates of the Earth’s surface as well as generating intensity values. Nationwide airborne laser scanning was launched in Finland in 2008 and some 180 000 km2 had been scanned by the end of 2012. While the main goal in this endeavour is to produce an accurate digital elevation/terrain model (2 x 2 m2 grid size) of the whole of the country, other applications, e.g. forestry, will benefit from the data as well. This study deals with the accuracy of airborne laser scanning, the optimization of the scanning angle, and the calibration of intensity. Accuracy assessments of airborne laser scanning have shown that the geometric accuracy of the method can fulfill the accuracy requirements for producing a nationwide digital elevation model with a grid of 2 x 2 m2. When studying the effect of scanning angle and biomass on elevation modeling capability, it was found that it would be possible to increase the scanning angle applied in Finland’s nationwide laser scanning. Even though the accuracy of the elevation model in the conditions prevailing in Finland allows increasing of the scanning angle, other applications would most probably not benefit from this. For example, these same data are sometimes used in nationwide forest inventory in Finland. A method for relative and absolute calibration of airborne laser scanning intensity was developed. The portable reference targets have proved their usefulness for calibration purposes. An intensity correction method should be used in pre-processing the airborne laser data. As a result of this, the usability of the intensity values may increase in practical applications, such as in classification. The studies constituting this dissertation have already impacted on the practical aspects of the nationwide airborne laser scanning dealing with accuracy assessment, the work done in the field of intensity calibration, and scanning angle analysis may have a further impact on nationwide laser scanning in the coming years. The optimization of airborne laser scanning flight parameters for multi-use nationwide laser scanning is a topic deserving further research.Ilmasta tehtävä laserkeilaus tuottaa 3D-koordinaatteja maan pinnalta sekä intensiteettiarvoja. Suomen valtakunnallinen laserkeilaus aloitettiin vuonna 2008 ja noin 180000 km2 oli keilattu vuoden 2012 loppuun mennessä. Vaikka päätarkoituksena on tuottaa tarkka digitaalinen korkeus/maastomalli (2 x 2 m2 ruutukoko) koko maasta, muutkin sovellukset, kuten metsätalous, hyötyvät tästä aineistosta. Tämä tutkimus käsittelee ilmasta tehtävän laserkeilauksen tarkkuutta, keilauskulman optimointia sekä intensiteetin kalibrointia. Laserkeilauksen tarkkuusarviointi on osoittanut, että menetelmän geometrinen tarkkuus täyttää valtakunnallisen digitaalisen korkeusmallin tuottamisen tarkkuusvaatimukset. Kun tutkittiin keilauskulman ja biomassan vaikutusta korkeusmallin tuottamiseen, huomattiin että olisi mahdollista kasvattaa valtakunnallisen laserkeilauksen havaintokulmaa. Vaikka korkeusmallin tarkkuus mahdollistaisi Suomen oloissa keilauskulman kasvattamisen, muut sovellukset eivät luultavasti hyötyisi tästä. Esimerkiksi tätä samaa aineistoa käytetään Suomen valtakunnallisessa metsien inventoinnissa. Laserkeilauksen intensiteetin suhteellista ja absoluuttista kalibrointia varten kehitettiin menetelmä. Siirrettävät referenssikohteet osoittivat käyttökelpoisuutensa intensiteetin kalibroinnissa. Intensiteetin kalibrointimenetelmää tulisi käyttää laserkeilausaineiston esikäsittelyssä. Tämän tuloksena intensiteettiarvojen käyttökelpoisuus kasvaisi käytännön sovelluksissa, kuten luokittelussa. Tämän väitöskirjan muodostaneet tutkimukset ovat jo käytännössä vaikuttaneet valtakunnallisen laserkeilauksen tarkkuusarvioinnissa. Intensiteetin kalibrointityö ja keilauskulman analysointi vaikuttanevat valtakunnalliseen laserkeilaukseen tulevina vuosina. Lisätutkimusta tarvitaan ilmasta tehtävän laserkeilauksen lentoparametrien optimoimiseksi monikäyttöistä valtakunnallista laserkeilausta varten

Automated Extraction of 3D Building Windows from Mobile LiDAR Data

The three-dimensional (3D) city models have gained more and more attentions because of their considerable potential applications at present. In particular, the demands for Level of Detail (LoD) building models become urgent. Mobile Laser Scanning (MLS) has supplied a brand-new technology in the acquisition and update of 3D information in urban off-terrain features, particularly for building façade details. Accordingly, generating LoD3 building models from MLS point clouds becomes a new trend in recent studies. As a consequence, a method that can accurately and automatically extract 3D windows from raw MLS point clouds is presented in this thesis. To provide solid and credible information for LoD3 building models, this automated method endeavors to identify window frames on building facades from MLS point clouds. This algorithm can typically be regarded as a stepwise procedure to interpret MLS point clouds as semantic features. A voxel-based upward-growing method is firstly applied to distinguish non-ground points from ground points. Noise is then filtered out from non-ground points by statistical analysis. In order to segment out the building facades, all the remaining non-ground points are clustered based on conditional Euclidean clustering algorithm; clusters whose density and width are over a given threshold will be designated as points for building facades. After a building façade is successfully extracted, a volumetric box is created to contain façade points so that neighbours of each point can be operated. A manipulator is finally applied according to the structural characteristics of window frames to extract the potential window points. The experimental results demonstrate that the proposed algorithm can successfully extract the rectangular or curved windows in the test datasets with promising accuracies. The 2D validation and 3D validation were both conducted in this study. In the 2D validation, the lowest F-measure of the test datasets is 0.740, and the highest can be 0.977. While in the 3D validation, the lowest correctness of the test dataset is 79.58%, and the highest can be 97.96%. After further analysis of the experimental results, it was found that, for those windows concave on walls or with curtains drawn, the performance of the proposed method was influenced. Furthermore, big holes caused by system errors in raw point clouds also had negative impacts on the proposed method. In conclusion, this thesis makes a considerable contribution to extracting 3D rectangular, irregular and arc-rounded windows from noisy MLS point clouds with high accuracy and high efficiency. It has supplied a promising method for generating LoD3 building models

Semi-automated Generation of Road Transition Lines Using Mobile Laser Scanning Data

Recent advances in autonomous vehicles (AVs) are exponential. Prominent car manufacturers, academic institutions, and corresponding governmental departments around the world are taking active roles in the AV industry. Although the attempts to integrate AV technology into smart roads and smart cities have been in the works for more than half a century, the High Definition Road Maps (HDRMs) that assists full self-driving autonomous vehicles did not yet exist. Mobile Laser Scanning (MLS) has enormous potential in the construction of HDRMs due to its flexibility in collecting wide coverage of street scenes and 3D information on scanned targets. However, without proper and efficient execution, it is difficult to generate HDRMs from MLS point clouds. This study recognizes the research gaps and difficulties in generating transition lines (the paths that pass through a road intersection) in road intersections from MLS point clouds. The proposed method contains three modules: road surface detection, lane marking extraction, and transition line generation. Firstly, the points covering road surface are extracted using the voxel- based upward-growing and the improved region growing. Then, lane markings are extracted and identified according to the multi-thresholding and the geometric filtering. Finally, transition lines are generated through a combination of the lane node structure generation algorithm and the cubic Catmull-Rom spline algorithm. The experimental results demonstrate that transition lines can be successfully generated for both T- and cross-intersections with promising accuracy. In the validation of lane marking extraction using the manually interpreted lane marking points, the method can achieve 90.80% precision, 92.07% recall, and 91.43% F1-score, respectively. The success rate of transition line generation is 96.5%. Furthermore, the Buffer-overlay-statistics (BOS) method validates that the proposed method can generate lane centerlines and transition lines within 20 cm-level localization accuracy from MLS point clouds. In addition, a comparative study is conducted to indicate the better performance of the proposed road marking extraction method than that of three other existing methods. In conclusion, this study makes a considerable contribution to the research on generating transition lines for HDRMs, which further contributes to the research of AVs