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Titlebook: Research in Shape Modeling; Los Angeles, July 20 Kathryn Leonard,Sibel Tari Conference proceedings 2015 The Editor(s) (if applicable) and T

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書目名稱Research in Shape Modeling
副標題Los Angeles, July 20
編輯Kathryn Leonard,Sibel Tari
視頻videohttp://file.papertrans.cn/829/828007/828007.mp4
概述Demonstrates the latest techniques in analysis of shapes and shape metrics, providing a resource for further research in the growing field of mathematical shape modeling.First volume in Springer‘s new
叢書名稱Association for Women in Mathematics Series
圖書封面Titlebook: Research in Shape Modeling; Los Angeles, July 20 Kathryn Leonard,Sibel Tari Conference proceedings 2015 The Editor(s) (if applicable) and T
描述This is a new edited volume on shape analysis presenting results in shape modeling and computational geometry from the 2013 Association for Women in Mathematics (AWM)?symposium held at UCLA‘s Institute for Pure and Applied Mathematics (IPAM). In-depth discussion of shape modeling techniques is supplemented by full-color illustrations demonstrating the results of workshop-developed shape modeling algorithms. It will be the first volume?in Springer‘s AWM series.
出版日期Conference proceedings 2015
關鍵詞computational geometry; computer graphics; computer vision; shape modeling; spectral and spatial analysi
版次1
doihttps://doi.org/10.1007/978-3-319-16348-2
isbn_softcover978-3-319-36263-2
isbn_ebook978-3-319-16348-2Series ISSN 2364-5733 Series E-ISSN 2364-5741
issn_series 2364-5733
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Association for Women in Mathematics Serieshttp://image.papertrans.cn/r/image/828007.jpg
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Conference proceedings 2015athematics (AWM)?symposium held at UCLA‘s Institute for Pure and Applied Mathematics (IPAM). In-depth discussion of shape modeling techniques is supplemented by full-color illustrations demonstrating the results of workshop-developed shape modeling algorithms. It will be the first volume?in Springer
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Automatic Prior Shape Selection for Image Segmentation,aches assume known prior shape and segmentation results rely on the selection of prior shape. In this paper, we study how to do simultaneous automatic prior shape selection and segmentation in a variational scheme.
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Part-Aware Distance Fields for Easy Inbetweening in Arbitrary Dimensions, aim is to investigate whether in-betweens may be defined as ordinary averages once a proper shape representation (e.g. a part aware field) is established. The constructions are independent of the dimension of the space in which the shape is embedded as well as the number of shapes to be averaged.
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