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- 摘要
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- 实验方案
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Recovering Missing Trajectory Data for Mobile Laser Scanning Systems
摘要： Trajectory data are often used as important auxiliary information in preprocessing and extracting the target from mobile laser scanning data. However, the trajectory data stored independently may be lost and destroyed for various reasons, making the data unavailable for the relevant models. This study proposes recovering the trajectory of the scanner from point cloud data following the scanning principles of a rotating mirror. Two approaches are proposed from di?erent input conditions: Ordered three-dimensional coordinates of point cloud data, with and without acquisition time. We recovered the scanner’s ground track through road point density analysis and restored the position of the center of emission of the laser based on plane reconstruction on a single scanning line. The validity and reliability of the proposed approaches were veri?ed in the four typical urban, rural, winding, and viaduct road environments using two systems from di?erent manufacturers. The result deviations of the ground track and scanner trajectory from their actual position were a few centimeters and less than 1 decimeter, respectively. Such an error is su?ciently small for the trajectory data to be used in the relevant algorithms.
关键词： point density,scanner trajectory,scanning line,mobile laser scanning
更新于2025-09-23 15:21:01
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Accurate derivation of stem curve and volume using backpack mobile laser scanning
摘要： Forest inventories rely on field plots, the measurement of which is costly and time consuming by manual means. Thus, there is a need to automate plot-level field data collection. Mobile laser scanning has yet to be demonstrated for deriving stem curve and volume from standing trees with sufficient accuracy for supporting forest inventory needs. We tested a new approach based on pulse-based backpack mobile laser scanner (Riegl VUX-1HA) combined with in-house developed SLAM (Simultaneous Localization and Mapping), and a novel post-processing algorithm chain that allows one to extract stem curves from scan-line arcs corresponding to individual standing trees. The post-processing step included, among others, an algorithm for scan-line arc extraction, a stem inclination angle correction and an arc matching algorithm correcting for the drifts that are still present in the stem points after applying the SLAM algorithm. By using the stem curves defined by the detected arcs and tree heights provided by the pulse-based scanner, stem volume estimates for standing trees in easy (n = 40) and medium (n = 37) difficult boreal forest were calculated. In the easy and medium plots, 100% of pine and birch stems were correctly detected. The total RMSE of the extracted stem curves was 1.2 cm (5.1%) and 1.7 cm (6.7%) for the easy and medium plots, respectively. The RMSE were 1.8 m (8.7%) and 1.1 m (4.9%) for the estimated tree heights, and 9.7% and 10.9% for the stem volumes for the easy and medium plots, correspondingly. Thus, our processing chain provided stem volume estimates with a better accuracy than previous methods based on mobile laser scanning data. Importantly, the accuracy of stem volume estimation was comparable to that provided by terrestrial laser scanning approaches in similar forest conditions. To further demonstrate the performance of the proposed method, we compared our results against stem volumes calculated using the standard Finnish allometric volume model, and found that our method provided more accurate volume estimates for the two test sites. The findings are important steps towards future individual-tree-based airborne laser scanning inventories which currently lack cost-efficient and accurate field reference data collection techniques. The tree geometry defined by the stem curve is also an important input parameter for deriving quality-related information from trees. Forest management decision making will benefit from improvements to the efficiency and quality of individual tree reference information.
关键词： SLAM,Tree volume,Mobile laser scanning,Stem curve,Stem volume,Mobile
更新于2025-09-23 15:19:57
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Design and Evaluation of a Permanently Installed Plane-Based Calibration Field for Mobile Laser Scanning Systems
摘要： Mobile laser scanning has become an established measuring technique that is used for many applications in the fields of mapping, inventory, and monitoring. Due to the increasing operationality of such systems, quality control w.r.t. calibration and evaluation of the systems becomes more and more important and is subject to on-going research. This paper contributes to this topic by using tools from geodetic configuration analysis in order to design and evaluate a plane-based calibration field for determining the lever arm and boresight angles of a 2D laser scanner w.r.t. a GNSS/IMU unit (Global Navigation Satellite System, Inertial Measurement Unit). In this regard, the impact of random, systematic, and gross observation errors on the calibration is analyzed leading to a plane setup that provides accurate and controlled calibration parameters. The designed plane setup is realized in the form of a permanently installed calibration field. The applicability of the calibration field is tested with a real mobile laser scanning system by frequently repeating the calibration. Empirical standard deviations of <1 ... 1.5 mm for the lever arm and <0.005? for the boresight angles are obtained, which was priorly defined to be the goal of the calibration. In order to independently evaluate the mobile laser scanning system after calibration, an evaluation environment is realized consisting of a network of control points as well as TLS (Terrestrial Laser Scanning) reference point clouds. Based on the control points, both the horizontal and vertical accuracy of the system is found to be < 10 mm (root mean square error). This is confirmed by comparisons to the TLS reference point clouds indicating a well calibrated system. Both the calibration field and the evaluation environment are permanently installed and can be used for arbitrary mobile laser scanning systems.
关键词： plane-based calibration field,evaluation,configuration analysis,mobile laser scanning,control points,accuracy,TLS reference point clouds,boresight angles,controllability,lever arm
更新于2025-09-23 15:19:57
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A multi-faceted CNN architecture for automatic classification of mobile LiDAR data and an algorithm to reproduce point cloud samples for enhanced training
摘要： Mobile Laser Scanning (MLS) data of outdoor environment are typically characterised by occlusion, noise, clutter, large data size and high quantum of information which makes their classification a challenging problem. This paper presents three deep Convolutional Neural Network (CNN) architectures in three dimension (3D), namely single CNN (SCN), multi-faceted CNN (MFC) and MFC with reproduction (MFCR) for automatic classification of MLS data. The MFC uses multiple facets of an MLS sample as inputs to different SCNs, thus providing additional information during classification. The MFC, once trained, is used to reproduce additional samples with the help of existing samples. The reproduced samples are employed to further refine the MFC training parameters, thus giving a new method called MFCR. The three architectures are evaluated on an ensemble of 3D outdoor MLS data consisting of four classes, i.e. tree, pole, house and ground covered with low vegetation along with car samples from KITTI dataset. The total accuracy and kappa values of classifications reached up to (i) 86.0% and 81.3% for the SCN (ii) 94.3% and 92.4% for the MFC and (iii) 96.0% and 94.6% for the MFCR, respectively. The paper has demonstrated the use of multiple facets to significantly improve classification accuracy over the SCN. Finally, a unique approach has been developed for reproduction of samples which has shown potential to improve the accuracy of classification. Unlike previous works on the use of CNN for structured point cloud of indoor objects, this work shows the utility of different proposed CNN architectures for classification of varieties of outdoor objects, viz., tree, pole, house and ground which are captured as unstructured point cloud by MLS.
关键词： Sample reproduction,Mobile Laser Scanning (MLS),Automatic classification,Convolutional Neural Network (CNN)
更新于2025-09-19 17:15:36
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Review of mobile laser scanning target‐free registration methods for urban areas using improved error metrics
摘要： Registration is one of the most important tasks in mobile laser scanning (MLS) point cloud processing. This paper ?rstly reviews existing target-free matching techniques as well as methods to evaluate the quality of the registration. Next, a new error metric is introduced that takes into account the residuals of check planes as well as their orientation. Experiments using real datasets in combination with reference data were performed to evaluate the suitability of these metrics. The proposed error metric proved to be more suitable for evaluating the quality of point cloud registration than state-of-the-art equivalents. The results also indicate that least squares plane ?tting is the best technique for MLS point cloud registration.
关键词： point cloud matching,target-free registration,matching quality,error metric,mobile laser scanning
更新于2025-09-19 17:13:59
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Automated Method for Detection of Missing Road Point Regions in Mobile Laser Scanning Data
摘要： The paper proposes a method supported by MATLAB for detection and measurement of missing point regions (MPR) which may cause severe road information loss in mobile laser scanning (MLS) point clouds. First, the scan-angle thresholds are used to segment the road area for MPR detection. Second, the segmented part is mapped onto a binary image with a pixel size of ε through rasterization. Then, MPR featuring connected 1-pixels are identi?ed and measured via image processing techniques. Finally, the parameters regarding MPR in the image space are reparametrized in relation to the vehicle path recorded in MLS data for a better understanding of MPR properties on the geodetic plane. Tests on two MLS datasets show that the output of the proposed approach can e?ectively detect and assess MPR in the dataset. The ε parameter exerts a substantial in?uence on the performance of the method, and it is recommended that its value should be optimized for accurate MPR detections.
关键词： occlusion,image processing,missing points,point cloud,mobile laser scanning
更新于2025-09-16 10:30:52
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Using Weighted Total Least Squares and 3-D Conformal Coordinate Transformation to Improve the Accuracy of Mobile Laser Scanning
摘要： With the aid of global position system (GPS), mobile laser scanning (MLS) is able to provide 3-D geo-referenced point cloud that has centimeter-level accuracy. The MLS accuracy, however, degrades signi?cantly due to the trajectory errors of the laser scanner and the residual systematic errors from the geo-referencing transformation process in the GPS-free environments. To solve this problem, this article presents a novel integration algorithm based on the weighted total least squares (WTLS) and the 3-D conformal coordinate transformation (3DCCT). In this new method, the 3-D point measurement model and the error propagation parameter vector in the MLS can be updated in real-time, and they can also adjust the geo-referenced coordinate transformation parameters and eliminate the in?uences of the residual systematic errors during MLS. In this article, the MLS mathematical model is ?rst established, followed up by a detailed analysis for MLS error budget interpreting the effects of the individual error sources. Second, WTLS is used to correct the 3-D point measurement model of MLS and the error of propagation parameter vector; 3DCCT, WTLS, and ground control target feature constraints are applied to eliminate the residual systematic errors in the geo-referencing transformation process. Finally, several data sets from outdoor scenarios are used to evaluate and validate the proposed method. The experimental results demonstrate that the proposed method can signi?cantly improve the overall accuracy of the MLS system.
关键词： mobile laser scanning (MLS),weighted total least squares (WTLS),3-D conformal coordinate transformation (3DCCT)
更新于2025-09-16 10:30:52
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Tunnel Monitoring and Measuring System Using Mobile Laser Scanning: Design and Deployment
摘要： The common statistical methods for rail tunnel deformation and disease detection usually require a large amount of equipment and manpower to achieve full section detection, which are time consuming and ine?cient. The development trend in the industry is to use laser scanning for full section detection. In this paper, a design scheme for a tunnel monitoring and measuring system with laser scanning as the main sensor for tunnel environmental disease and deformation analysis is proposed. The system provides functions such as tunnel point cloud collection, section deformation analysis, dislocation analysis, disease extraction, tunnel and track image generation, roaming video generation, etc. Field engineering indicated that the repeatability of the convergence diameter detection of the system can reach ±2 mm, dislocation repeatability can reach ±3 mm, the image resolution is about 0.5 mm/pixel in the ballast part, and the resolution of the inner wall of the tunnel is about 1.5 mm/pixel. The system can include human–computer interaction to extract and label diseases or appurtenances and support the generation of thematic disease maps. The developed system can provide important technical support for deformation and disease detection of rail transit tunnels.
关键词： orthophoto image,convergence diameter,disease marking,mobile laser scanning,roaming video,dislocation
更新于2025-09-16 10:30:52
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Identification of trees and their trunks from mobile laser scanning data of roadway scenes
摘要： Trees along the roads are important assets, which need continuous assessment and maintenance. The mobile laser scanning (MLS) has been adopted as mainstream mapping technique for three-dimensional data acquisition along the roads. In this study, an automated method was developed to identify trees and their trunks from MLS data. A bottom-up search in two stages is adopted in the cylinders, which are formed by partitioning of normalized MLS data. Tree trunk is identified first based on linearity and data distribution homogeneity along lower section of object clusters lying near to the respective cylinder’s base centre. Then, crown of tree is retrieved for respective identified trunk using compactness index for circular or near-circular cross section of crown and its axial symmetry about trunk axis. The object cluster composed of trunk and crown both are identified as tree. The proposed method was tested and validated on MLS data of two different roadway test sites that were acquired at different point spacing. The results reveal that the performance of proposed method in these two sites in terms of average completeness, correctness, and F1 measure was 94.4%, 100%, and 97.1%, respectively. The correctness did not change in both sites and it was 100% and stable, which showed that none of the non-tree objects was falsely identified as tree and correctness in trees identification the test site complexity. The proposed method holds great potential for identifying trees from MLS data of various roadway site conditions, where shapes and sizes of trees in their 3D data get distorted due to occlusions, and partial overlap presents among objects. Furthermore, the proposed method was implemented in the graphics processing unit-based parallel computing framework and runtime was dramatically minimized on MLS datasets of two test sites.
关键词： tree identification,trunk detection,crown retrieval,roadway scenes,parallel computing,Mobile laser scanning
更新于2025-09-12 10:27:22
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Metro gauge inspection system based on mobile laser scanning technology
摘要： Detecting metro gauge is very important for the safe operation of the subway. In this study, we design a low-cost metro tunnel mobile scanning system (MDS-TJ-1), which integrates a laser profile scanner with an inertial measure unit and an odometer to provide positioning and attitude parameters of the trajectory. The Lagrange interpolation is used to accomplish the time unification of different sensors. A dynamic alignment scheme for profile scanner is proposed based on the designed plane reflector target with high reflectivity. The error accumulation of the odometer is corrected by recognising the tunnel longitudinal joints, and finish the multi-source data fusion. The horizontal ray method is developed to process the metro gauge inspection. The experiment results show that the alignment accuracy of scanner is within 8 mm, the inner coincidence of the point cloud is within 3 cm, and the average error of the gauge inspection is 7.8 mm.
关键词： Alignment,Data fusion,Gauge inspection,Point cloud,Mobile laser scanning,Metro tunnel,Multi-sensors
更新于2025-09-12 10:27:22