A Pipeline of 3D Scene Reconstruction from Point Clouds

3D technologies are becoming increasingly popular as their applications in industrial, consumer, entertainment, healthcare, education, and governmental increase in number. According to market predictions, the total 3D modeling and mapping market is expected to grow from $1.1 billion in 2013 to$7.7 billion by 2018. Thus, 3D modeling techniques for different data sources are urgently needed. This thesis addresses techniques for automated point cloud classification and the reconstruction of 3D scenes (including terrain models, 3D buildings and 3D road networks). First, georeferenced binary image processing techniques were developed for various point cloud classifications. Second, robust methods for the pipeline from the original point cloud to 3D model construction were proposed. Third, the reconstruction for the levels of detail (LoDs) of 1-3 (CityGML website) of 3D models was demonstrated. Fourth, different data sources for 3D model reconstruction were studied. The strengths and weaknesses of using the different data sources were addressed. Mobile laser scanning (MLS), unmanned aerial vehicle (UAV) images, airborne laser scanning (ALS), and the Finnish National Land Survey’s open geospatial data sources e.g. a topographic database, were employed as test data. Among these data sources, MLS data from three different systems were explored, and three different densities of ALS point clouds (0.8, 8 and 50 points/m2) were studied. The results were compared with reference data such as an orthophoto with a ground sample distance of 20cm or measured reference points from existing software to evaluate their quality. The results showed that 74.6% of building roofs were reconstructed with the automated process. The resulting building models provided an average height deviation of 15 cm. A total of 6% of model points had a greater than one-pixel deviation from laser points. A total of 2.5% had a deviation of greater than two pixels. The pixel size was determined by the average distance of input laser points. The 3D roads were reconstructed with an average width deviation of 22 cm and an average height deviation of 14 cm. The results demonstrated that 93.4% of building roofs were correctly classified from sparse ALS and that 93.3% of power line points are detected from the six sets of dense ALS data located in forested areas. This study demonstrates the operability of 3D model construction for LoDs of 1-3 via the proposed methodologies and datasets. The study is beneficial to future applications, such as 3D-model-based navigation applications, the updating of 2D topographic databases into 3D maps and rapid, large-area 3D scene reconstruction. 3D-teknologiat ovat tulleet yhä suositummiksi niiden sovellusalojen lisääntyessä teollisuudessa, kuluttajatuotteissa, terveydenhuollossa, koulutuksessa ja hallinnossa. Ennusteiden mukaan 3D-mallinnus- ja -kartoitusmarkkinat kasvavat vuoden 2013 1,1 miljardista dollarista 7,7 miljardiin vuoteen 2018 mennessä. Erilaisia aineistoja käyttäviä 3D-mallinnustekniikoita tarvitaankin yhä enemmän. Tässä väitöskirjatutkimuksessa kehitettiin automaattisen pistepilviaineiston luokittelutekniikoita ja rekonstruoitiin 3D-ympäristöja (maanpintamalleja, rakennuksia ja tieverkkoja). Georeferoitujen binääristen kuvien prosessointitekniikoita kehitettiin useiden pilvipisteaineistojen luokitteluun. Työssä esitetään robusteja menetelmiä alkuperäisestä pistepilvestä 3D-malliin eri CityGML-standardin tarkkuustasoilla. Myös eri aineistolähteitä 3D-mallien rekonstruointiin tutkittiin. Eri aineistolähteiden käytön heikkoudet ja vahvuudet analysoitiin. Testiaineistona käytettiin liikkuvalla keilauksella (mobile laser scanning, MLS) ja ilmakeilauksella (airborne laser scanning, ALS) saatua laserkeilausaineistoja, miehittämättömillä lennokeilla (unmanned aerial vehicle, UAV) otettuja kuvia sekä Maanmittauslaitoksen avoimia aineistoja, kuten maastotietokantaa. Liikkuvalla laserkeilauksella kerätyn aineiston osalta tutkimuksessa käytettiin kolmella eri järjestelmällä saatua dataa, ja kolmen eri tarkkuustason (0,8, 8 ja 50 pistettä/m2) ilmalaserkeilausaineistoa. Tutkimuksessa saatuja tulosten laatua arvioitiin vertaamalla niitä referenssiaineistoon, jona käytettiin ortokuvia (GSD 20cm) ja nykyisissä ohjelmistoissa olevia mitattuja referenssipisteitä. 74,6 % rakennusten katoista saatiin rekonstruoitua automaattisella prosessilla. Rakennusmallien korkeuksien keskipoikkeama oli 15 cm. 6 %:lla mallin pisteistä oli yli yhden pikselin poikkeama laseraineiston pisteisiin verrattuna. 2,5 %:lla oli yli kahden pikselin poikkeama. Pikselikoko määriteltiin kahden laserpisteen välimatkan keskiarvona. Rekonstruoitujen teiden leveyden keskipoikkeama oli 22 cm ja korkeuden keskipoikkeama oli 14 cm. Tulokset osoittavat että 93,4 % rakennuksista saatiin luokiteltua oikein harvasta ilmalaserkeilausaineistosta ja 93,3 % sähköjohdoista saatiin havaittua kuudesta tiheästä metsäalueen ilmalaserkeilausaineistosta. Tutkimus demonstroi 3D-mallin konstruktion toimivuutta tarkkuustasoilla (LoD) 1-3 esitetyillä menetelmillä ja aineistoilla. Tulokset ovat hyödyllisiä kehitettäessä tulevaisuuden sovelluksia, kuten 3D-malleihin perustuvia navigointisovelluksia, topografisten 2D-karttojen ajantasaistamista 3D-kartoiksi, ja nopeaa suurten alueiden 3D-ympäristöjen rekonstruktiota

Uses and Challenges of Collecting LiDAR Data from a Growing Autonomous Vehicle Fleet: Implications for Infrastructure Planning and Inspection Practices

Autonomous vehicles (AVs) that utilize LiDAR (Light Detection and Ranging) and other sensing technologies are becoming an inevitable part of transportation industry. Concurrently, transportation agencies are increasingly challenged with the management and tracking of large-scale highway asset inventory. LiDAR has become popular among transportation agencies for highway asset management given its advantage over traditional surveying methods. The affordability of LiDAR technology is increasing day by day. Given this, there will be substantial challenges and opportunities for the utilization of big data resulting from the growth of AVs with LiDAR. A proper understanding of the data size generated from this technology will help agencies in making decisions regarding storage, management, and transmission of the data. The original raw data generated from the sensor shrinks a lot after filtering and processing following the Cache county Road Manual and storing into ASPRS recommended (.las) file format. In this pilot study, it is found that while considering the road centerline as the vehicle trajectory larger portion of the data fall into the right of way section compared to the actual vehicle trajectory in Cache County, UT. And there is a positive relation between the data size and vehicle speed in terms of the travel lanes section given the nature of the selected highway environment

A review of laser scanning for geological and geotechnical applications in underground mining

Laser scanning can provide timely assessments of mine sites despite adverse challenges in the operational environment. Although there are several published articles on laser scanning, there is a need to review them in the context of underground mining applications. To this end, a holistic review of laser scanning is presented including progress in 3D scanning systems, data capture/processing techniques and primary applications in underground mines. Laser scanning technology has advanced significantly in terms of mobility and mapping, but there are constraints in coherent and consistent data collection at certain mines due to feature deficiency, dynamics, and environmental influences such as dust and water. Studies suggest that laser scanning has matured over the years for change detection, clearance measurements and structure mapping applications. However, there is scope for improvements in lithology identification, surface parameter measurements, logistic tracking and autonomous navigation. Laser scanning has the potential to provide real-time solutions but the lack of infrastructure in underground mines for data transfer, geodetic networking and processing capacity remain limiting factors. Nevertheless, laser scanners are becoming an integral part of mine automation thanks to their affordability, accuracy and mobility, which should support their widespread usage in years to come

Vision and advocacy of optoelectronic technology developments in the AECO sector

Purpose This research presents a literature review of laser scanning and 3D modelling devices, modes of delivery and applications within the architecture, engineering, construction and owner-operated (AECO) sector. Such devices are inextricably linked to modern digital built environment practices, particularly when used in conjunction with as-built building information modelling (BIM) development. The research also reports upon innovative technological advancements (such as machine vision) that coalesce with 3D scanning solutions. Design/methodology/approach A synthesis of literature is used to develop: a hierarchy of the modes of delivery for laser scan devices; a thematic analysis of 3D terrestrial laser scan technology applications; and a componential cross-comparative tabulation of laser scan technology and specifications. Findings Findings reveal that the costly and labour intensive attributes of laser scanning devices have stimulated the development of hybrid automated and intelligent technologies to improve performance. Such developments are set to satisfy the increasing demand for digitisation of both existing and new buildings into BIM. Future work proposed will seek to: review what coalescence of digital technologies will provide an optimal and cost effective solution to accurately reconstructing the digital built environment; conduct case studies that implement hybrid digital solutions in pragmatic facilities management scenarios to measure their performance and user satisfaction; and eliminate manual remodelling tasks (such as point cloud reconstruction) via the use of computational intelligence algorithms integral within cloud based BIM platforms. Originality/value Although laser scanning and 3D modelling have been widely covered en passant within the literature, scant research has conducted an holistic review of the technology, its applications and future developments. This review presents concise and lucid reference guidance that will intellectually challenge, and better inform, both practitioners and researchers

Automated 3D scene reconstruction from open geospatial data sources: airborne laser scanning and a 2D topographic database

Open geospatial data sources provide opportunities for low cost 3D scene reconstruction. In this study, based on a sparse airborne laser scanning (ALS) point cloud (0.8 points/m2) obtained from open source databases, a building reconstruction pipeline for CAD building models was developed. The pipeline includes voxel-based roof patch segmentation, extraction of the key-points representing the roof patch outline, step edge identification and adjustment, and CAD building model generation. The advantages of our method lie in generating CAD building models without the step of enforcing the edges to be parallel or building regularization. Furthermore, although it has been challenging to use sparse datasets for 3D building reconstruction, our result demonstrates the great potential in such applications. In this paper, we also investigated the applicability of open geospatial datasets for 3D road detection and reconstruction. Road central lines were acquired from an open source 2D topographic database. ALS data were utilized to obtain the height and width of the road. A constrained search method (CSM) was developed for road width detection. The CSM method was conducted by splitting a given road into patches according to height and direction criteria. The road edges were detected patch by patch. The road width was determined by the average distance from the edge points to the central line. As a result, 3D roads were reconstructed from ALS and a topographic database