Title: | Efficient pose deformations for human models in customized sizes and shapes |
Authors: | Zhu, Shuaiyin Mok, P. Y. |
Citation: | WSCG '2017: short communications proceedings: The 25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2016 in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech RepublicMay 29 - June 2 2017, p. 33-41. |
Issue Date: | 2017 |
Publisher: | Václav Skala - UNION Agency |
Document type: | konferenční příspěvek conferenceObject |
URI: | wscg.zcu.cz/WSCG2017/!!_CSRN-2702.pdf http://hdl.handle.net/11025/29732 |
ISBN: | 978-80-86943-45-9 |
ISSN: | 2464-4617 |
Keywords: | modelování člověka;deformace postoje;přístup založený na příkladech;přizpůsobení modelu;deformační přenos |
Keywords in different language: | human modelling;pose deformation;example-based approach;model customization;deformation transfer |
Abstract: | Modelling dynamic pose deformations of human subjects is an important topic in many research applications. Existing approaches of human pose deformations can be classified as volume-based, skeletal animation and example-based methods. These approaches have both strengths and limitations. However, for models in customized shapes, it is very challenging to deform these models into different poses rapidly and realistically. We 10 propose a conceptual model to realize rapid and realistic pose deformation to customized human models by the integration of skeletal-driven rigid deformation and example-learnt non-rigid surface deformation. Based on this framework, a method for rapid automatic pose deformation is developed to deform human models of various body shapes into a series of dynamic poses. A series of algorithms are proposed to complete the pose deformation automatically and efficiently, including automatic segmentation of body parts and skeleton embedding, skeletal15 driven rigid deformation, training of non-rigid deformation from pose dataset; shape mapping of non-rigid deformation, and integration of rigid and non-rigid deformations. Experiment has shown that the proposed method can customize accurate human models based on two orthogonal-view photos and also efficiently generate realistic pose deformations for the customized models. |
Rights: | © Václav Skala - UNION Agency |
Appears in Collections: | WSCG '2017: Short Papers Proceedings |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/29732
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