Curvature-based spectral signatures for non-rigid shape retrieval
نویسندگان
چکیده
منابع مشابه
Feature Encoding of Spectral Signatures for 3D Non-Rigid Shape Retrieval
A large number of local signatures have been created to represent local characteristics of geometric 3D shapes for the purpose of many computer vision, geometry processing and shape analysis tasks. A local signature is a compact representation that characterizes a small region of a shape. They usually capture information about the neighbourhood of a vertex and so they can be directly applied to...
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Reducing the setup time for a new production line is critical to the success of a manufacturer within the current competitive and cost-conscious market. To this end, being able to reuse already available machines, toolings and parts is paramount. However, matching a large warehouse of previously engineered parts to a new component to produce, is often more a matter of art and personal expertise...
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We present a new benchmark for testing algorithms that create canonical forms for use in non-rigid 3D shape retrieval. We have combined two existing datasets to create a varied collection of models for testing. Canonical forms attempt to factor out a shape’s pose, giving a pose-neutral shape. This opens up the possibility of using methods originally designed for rigid retrieval for the task of ...
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Non-rigid 3D shape retrieval has become an active and important research topic in contentbased 3D object retrieval. The aim of this paper is to measure and compare the performance of state-of-the-art methods for non-rigid 3D shape retrieval. The paper develops a new benchmark consisting of 600 non-rigid 3D watertight meshes, which are equally classified into 30 categories, to carry out experime...
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In this paper an approach to image compression based on shape based information is presented. The current shape based compression doesn’t exploit the curvature information and basically uses the shape region information for compressing the image. In this paper an approach to compress the image based on the shape information exploiting the external shape variations in representive features for i...
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ژورنال
عنوان ژورنال: Computer Vision and Image Understanding
سال: 2018
ISSN: 1077-3142
DOI: 10.1016/j.cviu.2018.04.002