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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 6 of 6 for “"Shape segmentation"”.
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Machine Learning Algorithms for Geometry Processing by Example
… Each algorithm takes as input a collection of shapes along with exemplar values of target properties related to shape processing tasks. The goal of the algorithms is to output a function that maps from the shape data to the target properties. The learned functions can be applied to novel input …
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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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On analysing deformable (moving) objects
… of perception of a visual scene.<br/><br/>Segmentation and matching are instrumental tasks in producing comparable features in applications such as medical imaging, mining and oil extraction, gaming consoles, face, ear and gait biometrics, and etc.<br/><br/>The ultimate goal of this study …
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Learning 3D Representations from Data
… high-level semantic reasoning tasks such as shape segmentation and 3D object detection. To that end, we propose a multi-view based object detection model that learns complementary features by projecting point clouds to virtual views. In addition, our follow-up work Object DGCNN leverages …
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Automatic segmentation of wall structures from cardiac images
… left atrium from MR images. As applications, the segmentation results are used to facilitate cardiac disease analysis. Specifically, 1. An automatic method is proposed to extract the ventricles from CT images by integrating surface decomposition with contour evolution techniques. In particular, …
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Segmentation And Spatial Depth Ridge Detection Of Unorganized Point Cloud Data
… we propose a methodology for approximating a shape's solid geometry using the unorganized 3D point cloud data of that shape primarily by utilizing localized principal component analysis information. Our model accounts for three comissues that arise in the scanning of 3D objects: noise in …