Intelligent Shape Editing with Robust Feature Analysis

Lead Research Organisation: Cardiff University
Department Name: Computer Science

Abstract

With the development of 3D acquisition techniques, geometric models are more and more widely available. Model editing is an effective way to generate new geometric models from existing ones. This project aims to develop a new editing framework based on robust feature analysis, which has been largely unexplored. We propose to study two related problems: robust feature analysis suitable for surface editing, and improving editing in both efficiency and quality with the guidance of features. Methods developed by the project will enable more effective editing to be carried out on triangular meshes, which has potential to be useful in wide application areas. The most direct applications are in Computer Graphics, where triangular meshes are widely used for rendering, animation and arts and Computer Aided Design, where such meshes are used to represent a variety of natural and designed shapes. Robust feature analysis techniques are fundamental to more general settings when geometric models are used, so the framework focussing on feature analysis and interactive techniques may also stimulate further research.

Planned Impact

The impact of the proposed work will exist in a variety of fields at different levels. The project will improve the understanding of geometric features, and their potential relationship and usefulness to editing. The relationship between image processing and geometry processing will be studied in various subareas; the insight will lead to further development and research. Potential end users will include e.g. game designers and animators in the entertainment industry, who will benefit from the techniques developed in the project by improving both their productivity and the quality of surface editing results. Software vendors producing packages for healthcare, artistic design and entertainment software will be able to enhance their current software to include new editing tool functionality, and improve existing tools. The project will be carried out in collaboration with an industrial partner: Delcam plc, a world leading supplier of CAD/CAM products, and in particular in their healthcare product lines, to e.g. improve the organic shape sculpting while preserving the geometry of functional features. The developed techniques will also be potentially useful to a variety of other applications e.g. cultural heritage protection.

Publications

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Gao L (2012) L p shape deformation in Science China Information Sciences

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Lai Y (2012) Vertex location optimisation for improved remeshing in Graphical Models

 
Description With the development of 3D acquisition techniques, geometric models are more and more widely available. Model editing is an effective way to generate new geometric models from existing ones. However, in traditional shape editing it is often tedious to select relevant regions of interest and to apply various editing operations. This project studies effective techniques based on feature analysis to facilitate intelligent shape editing that reduces the amount of user effort.

To allow more effective selection and editing, local geometric features as well as their relationship are exploited. We proposed a new approach that significantly improves globally consistent correspondence selection under the more general local isometric assumption using diffusion pruning. The method is hundreds of times more efficient in both time and memory costs than state of the art methods, and is more robust to incomplete scans and non-isometric deformation.

We also studied more flexible shape deformation techniques and proposed an approach using the general Lp norm instead of the traditional Euclidean (L2) norm, inspired by recent sparse signal reconstruction work. This gives an intuitive control of distortion distribution and achieves various editing results including those with better structure preservation. To facilitate efficient processing using multiresolution analysis, we also proposed a more effective point location approach for remeshing.

We have developed a prototype system to demonstrate the overall idea of improving shape editing using feature analysis. Four journal papers have been published, including one paper in ACM Transactions on Graphics (the top journal in computer graphics).

Robust feature analysis techniques are fundamental to more general settings when geometric models are used, so the framework focussing on feature analysis and interactive techniques may also stimulate further research.
Exploitation Route Methods developed by the project will enable more effective editing to be carried out on triangular meshes, which has potential to be useful in wide application areas. The most direct applications are in Computer Graphics, where triangular meshes are widely used for rendering, animation and arts.

We collaborate with Delcam, a world leading provider of CAD/CAM software, to potentially exploit the ideas and techniques for their products. With the work published in leading journals, we expect to attract interests from both academia and industry and build up links for potential collaboration.
Sectors Creative Economy,Digital/Communication/Information Technologies (including Software),Manufacturing, including Industrial Biotechology,Culture, Heritage, Museums and Collections

URL http://www.cs.cf.ac.uk/ShapeEditing/
 
Description Royal Society Newton Advanced Fellowship
Amount £110,710 (GBP)
Funding ID NA150431 
Organisation The Royal Society 
Sector Academic/University
Country United Kingdom
Start 03/2016 
End 02/2019
 
Description Royal Society Newton Mobility Grant
Amount £11,970 (GBP)
Funding ID IE150731 
Organisation The Royal Society 
Sector Academic/University
Country United Kingdom
Start 03/2016 
End 03/2018
 
Description Invited Talk (Tianjin, China) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact I gave an invited talk on the topic "3D Dynamic Shape Reconstruction and Modelling" based on the research findings in this project, to an audience of about 50 research/undergraduate students at Tianjin University, China. The talk led to questions and discussions afterwards.
Year(s) Of Engagement Activity 2016