Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 61 for “"point cloud data"”.
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Segmentation And Spatial Depth Ridge Detection Of Unorganized Point Cloud Data
Visual 3D data are of interest to a number of fields: medical professionals, game designers, graphic designers, and (in the interest of this paper) ichthyologists interested in the taxonomy of fish. Since the release of the Kinect for the Microsoft XBox, game designers have been interested in using …
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Quality assessment of 3D printed concrete through point cloud data analysis
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01
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Deep Learning-Based Part Labeling of Tree Components in Point Cloud Data
Point cloud data analysis plays a crucial role in forest management, remote sensing, and wildfire monitoring and mitigation, necessitating robust computer algorithms and pipelines for segmentation and labeling of tree components. This thesis presents a novel pipeline that employs deep learning …
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The Use of Image and Point Cloud Data in Statistical Process Control
The volume of data acquired in production systems continues to expand. Emerging imaging technologies, such as machine vision systems (MVSs) and 3D surface scanners, diversify the types of data being collected, further pushing data collection beyond discrete dimensional data. These large and diverse …
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SnapshotNet: Self-supervised Feature Learning for Point Cloud Data Segmentation Using Minimal Labeled Data
<p>Manually annotating complex scene point cloud datasets is both costly and error-prone. To reduce the reliance on labeled data, a new model called SnapshotNet is proposed as a self-supervised feature learning approach, which directly works on the unlabeled point cloud data of a complex 3D scene. …
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Semantically-rich as-built 3D modeling of the built environment from point cloud data
… mainly consists of three sequential steps: data collection, modeling, and analysis. In current practice, these steps are performed manually by surveyors, designers, and engineers. Such manual tasks can be time-consuming, prohibitively expensive, and are prone to errors. While the analysis …
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Automated Landing Site Evaluation for Semi-Autonomous Unmanned Aerial Vehicles
… unmanned aerial vehicle (UAV) from point cloud data obtained from a stereo vision system. The relatively inexpensive, commercially available Bumblebee stereo vision camera was selected for this study. A "point cloud viewer" computer program was written to analyze point cloud data …
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Application of unmanned aerial systems and deep learning in high-throughput plant phenotyping
… with various sensors provide high-resolution data for high-throughput plant phenotyping. UAS image-based machine learning algorithms have been applied in plant phenotyping. However, only limited studies have evaluated the performance of using deep learning and UAS imaging in cotton or plant …
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Adaptive slicing of cloud data for reverse engineering and direct rapid prototyping model construction
… engineering, conventional surface modelling from point cloud data is time-consuming and requires expert modelling skills. One of the innovative modelling methods is to directly slice the point cloud along a direction and generate a layer-based model, which can be used directly for fabrication …
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Modeling Forest Canopy Distribution from Ground-Based Laser Scanner Data
… and ranging (lidar) technology but gathers data at higher resolution over a more limited scale. The raw data consist of a series of range measurements to visible surfaces taken at known angles relative to the scanner. Data were translated into three dimensional (3D) point clouds with points …
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Automated Object Segmentation in Existing Industrial Facilities
Shape segmentation from point cloud data is a core step of the digital twinning process for industrial facilities. However, this process is labour-intensive with 90% of the cost being spent on converting point cloud data to a model. This counteracts the perceived value of the resulting model in …
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Novel Approach for Non-Invasive Prediction of Body Shape and Habitus
… a total joint replacement. Accurate movement data for subjects with a higher BMI is of the utmost importance because it can be used to inform treatment options for people who have received joint replacements or are waiting to receive a replacement. Currently, movement data from this subgroup …
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Multi-Domain Coincidence Processing and Memory Architecture for Real-Time Geiger Mode LiDAR
… These sensor arrays produce very high data rates on the order of 5 Gbps, requiring high-bandwidth motion compensation and coincidence processing to correlate the range returns and locate the modes in three-dimensional space. This paper proposes a multi-processor system architecture and …
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The mechanical and algorithmic design of in-field robotic leaf sampling device
… leaves with high horizontal level, (3) Combine point cloud data from the depth camera and vison data from the camera via the sensor fusion to get the leaf rolling angle and grasp point. The method in this thesis can produce a consistent leaf rolling angle estimate quantitatively and …
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Surface reconstruction of a blast plate using stereo vision
… the relationship between the views. The 3-D point is then estimated using triangulation of the corresponding points from the two views. The blast plates that are reconstructed have highly reflective surfaces. This causes a problem due to specular reflection. This thesis further studies the …
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The Scalability of X3D4 PointProperties: Benchmarks on WWW Performance
… researchers to acquire high-resolution point cloud data by themselves. There have been plenty of online tools for researchers to exhibit their work. However, the drawback of existing tools is that they are not flexible enough for the users to create 3D scenes of a mixture of point-based …
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Towards Estimating Friction Factors of Mine Drifts from Low Density Point Clouds
… By using a mobile LiDAR platform low density point clouds are collected then analysed to estimate the friction factor and are compared to those calculated from ventilation data gathered at Barrick Gold Corporation - Hemlo. The two original methods described, in addition to four previously …
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Development of UAV-based lidar crop height mapping system
… (LiDAR) sensor was capable of accurate and fast data collection. As technology of Unmanned Aerial Vehicles (UAV) advanced, the airborne LiDAR system became a promising remote sensing based method for non-destructive crop height measurement. The objective of this study was to develop a UAV-based …
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Automated Generation of Geometric Digital Twins of Existing Reinforced Concrete Bridges
… and effort of modelling existing bridges from point clouds currently outweighs the perceived benefits of the resulting model. The time required for generating a geometric Bridge Information Model, a holistic data model which has recently become known as a "Digital Twin", of an existing bridge …
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Automating the Generation of Geometric Information Models to Support Digital Twinning of Existing Rail Infrastructure
Geometric modelling from point cloud data is a fundamental step of the digital twinning process for rail infrastructure. Currently, this onerous procedure outweighs the anticipated benefits of the resulting model and expends 74% of the modellers’ effort on converting point cloud data to a model. …
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