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 51 for “"3D Point Cloud"”.
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On the 3D point cloud for human-pose estimation
… methodologies for estimating a human pose from a 3D point cloud that is captured by a static depth sensor. Human-pose estimation (HPE) is important for a range of applications, such as human-robot interaction, healthcare, surveillance, and so forth. Yet, HPE is challenging because of the …
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3D point cloud learning: a survey and a toolbox
… robotics, has brought increasing attention to 3D point cloud understanding. However, while deep learning methods obtained remarkable success in 2D image tasks, deep models on point clouds still suffer from unique challenges in processing unstructured points with deep neural networks. This …
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Registration of Arbitrary 3D Point Cloud Using Statistical Head Model
The standardization of arbitrary 3D head mesh is necessary for many applications. This project explores one possible standardization method which made used of traditional 3D registration techniques (i.e. the Iterative Closest Point algorithm) and a given statistical head mesh model. During the …
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Integrative and Multi-scale Deep Learning for 3D Point Cloud Transmission Corridor Scene Segmentation: Noise Filtering, Attention-Fused Feature Integration, and Panoptic Network
… It enables the acquisition of high-density 3D point clouds with pulse repetition frequencies ranging from 100Hz to 2MHz. However, the increased overlap with atmospheric points has posed challenges in noise filtering and 3D point cloud quality. This dissertation proposes the Noise Seeking …
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Virtual-Real Object Registration and Shape Completion for Stable and Accurate Augmented Reality Technology
… and has been widely used in many applications. 3D point cloud registration is one of the main processes to correctly align virtual 3D objects with real-world scenes in AR. The higher quality of the underlying 3D point clouds with fewer missing and noisy points, the more accurate the 3D point …
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The Mapkey: Preliminary Design, Construction and Testing of a Novel UAV Platform for Cavity Surveying
… unmanned aerial vehicle (UAV) for gathering 3D maps of underground cavities. The novel UAV is called "The Mapkey". Current underground cavity surveying is conducted by using a stationary light detection and ranging (LiDAR) sensor extended into a void to collect a 3D point cloud. This method …
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Supervoxel Based Object Detection and Seafloor Segmentation Using Novel 3d Side-Scan Sonar
… the side-scan sonar now produces a true 3D point cloud representation of the seafloor embedded with echo intensity. This creates a need to develop algorithms to process the incoming 3D data for applications such as object detection and segmentation, and an opportunity to leverage advances …
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Autonomous Sample Collection Using Image-Based 3D Reconstructions
… These are derived from data provided by colored 3D point clouds produced via image-based 3D reconstructions. A custom robotic mobility platform, the Scoopbot, is introduced to perform completely automated imaging of the sampling area and also to pick up the desired sample. The Scoopbot is …
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3D diffusion based generation model for point cloud annotation and generation
… with the rapid advancement of applications and 3D scanning sensors, the demand for 3D deep learning based technology and data has increased dramatically. Especially 3D shape with semantic labels plays a significant role in 3D vision problems, such as auto-driven, 3D object detection and 3D scene …
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Covariance based point cloud descriptors for object detection and classification
Processing 3D point data is of primary interest in many areas of computer vision, including object grasping, robot navigation, and 3D object recognition. The recent introduction of cheap range sensors like the Microsoft Kinect has created a great interest in the computer vision community towards …
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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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3D Deep Learning for Object-Centric Geometric Perception
… aims at extracting the geometric attributes of 3D objects. These attributes include shape, pose, and motion of the target objects, which enable fine-grained object-level understanding for various tasks in graphics, computer vision, and robotics. With the growth of 3D geometry data and 3D deep …
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Automatic Alignment of 3D Multi-Sensor Point Clouds
Automatic 3D point cloud alignment is a major research topic in photogrammetry, computer vision and computer graphics. In this research, two keypoint feature matching approaches have been developed and proposed for the automatic alignment of 3D point clouds, which have been acquired from different …
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Automatic Extraction of Joint Characteristics from Rock Mass Surface Point Cloud Using Deep Learning
… for a computerized recognition of joint sets on 3D point cloud models of rock masses using deep learning is presented. The process starts with classifying joints on a 3D rock mass surface through training a deep network architecture and validated using manually labelled datasets. Then, individual …
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Supportless Fabrication, Experimental, and Numerical Analysis of the Physical Properties for a Thin-Walled Hemisphere
… samples as input data. The other solution uses a 3D point cloud of the surface. The innovation of the 3D point cloud solution is the distance factor that is applied in the calculations. The results of this solution are compared to the mount solution. Since the input data of the mount solution is …
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Modeling Robotic Wire Arc Additive Manufacturing Process Using Machine Learning
… passes of the torch, much like conventional 3D printers. This proposal plans to improve the process by using a weaving toolpath. For characterization, a Cognex DS 1300R laser scanner will generate a 3D point cloud of the welds produced by the WAAM process with a resolution in the micrometer …
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Volumetric Attribute Compression for 3D Point Clouds using Feedforward Network with Geometric Attention
We study 3D point cloud attribute compression using a volumetric approach: given a target volumetric attribute function $f : \mathbb{R}^3 \rightarrow \mathbb{R}$, we quantize and encode parameter vector $\theta$ that characterizes $f$ at the encoder, for reconstruction $f_{\hat{\theta}}(\x)$ at …
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3D digital model reconstruction of insects from a single pair of stereoscopic images
… thesis proposes a robust method of creating a 3D digital model of an object through stereoscopic reconstruction. There are existing methods and tools for achieving this, but they tend to only perform well under favorable conditions, such as specializing to a specific class of objects or …
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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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An analysis of extracting cross sections from heritage site point clouds using meshfree point-based techniques
… age cultural heritage has evolved to incorporate 3D virtual models of heritage buildings and sites. It is common to use laser scanning to acquire the 3D point cloud data for these models, with this data usually being processed and “meshed” to form a surface mesh model, however, this process is …
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