Amplifiable Bi-directional Texture Functions for 3D High Fidelity Images
Lead Research Organisation:
Brunel University London
Department Name: Information Systems Computing and Maths
Abstract
This project is to investigate the techniques that use textures to enhance the exhibition of surface details in 3D computer generated images. It is generally recognised that one of the major differences between real world images and computer synthesized images lies in the exhibition of high-frequency visible surface details. This project will be an effort to bridge this major gap.The principal objective of this project is to develop a key technique called Amplifiable Bi-directional Texture Function (ABTF). ABTF is designed to generate textures on 3D surface models. Compared with the conventional texture mapping/synthesis techniques, ABTF will have the following strengths:1) It will not compromise on texture quality in close-up views; 2) It will accurately display significant visual effects of fine surface details, including self-shadowing and occlusion, inter-reflection and silhouettes, under different viewing/lighting settings.3) It will take into consideration the influence from the variations of target surface curvatures for the correct synthesis and display of textures. The ABTF synthesis will be based on a hybrid image modelling and rendering approach. Given multiple views of a texture sample, it will recover the underlying geometries of the texture and use them as surface details for the target surface. For high visual fidelity purpose, the colours of the target surface will be obtained from the images of the multiple views through a quick search scheme for achieving high quality and fast performance. The project has a wide range of potential applications. In fact, the range of use of 3D high fidelity images in different businesses and fields is surprisingly broad, which suggests a wide range of possible commercial application. Many 3D-related businesses have significant presence in the UK, and are playing an active role in the global market, e.g. computer games, computer animation, broadcast television, mobile communication, web design, etc., all of which are facing demands for improved image quality to take full advantage of continual advances in display technology.
Organisations
People |
ORCID iD |
Feng Dong (Principal Investigator) |
Publications
![publication icon](/resources/img/placeholder-60x60.png)
Chen D
(2008)
Adaptive Surface Texture Synthesis Using Round-Shaped Neighbourhoods
in Computer Graphics Forum
![publication icon](/resources/img/placeholder-60x60.png)
Chen D
(2010)
Shape from shading using wavelets and weighted smoothness constraints
in IET Computer Vision
![publication icon](/resources/img/placeholder-60x60.png)
Wang C
(2013)
Nonedge-specific adaptive scheme for highly robust blind motion deblurring of natural imagess.
in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
![publication icon](/resources/img/placeholder-60x60.png)
Wang C
(2013)
Enhancing Bayesian Estimators for Removing Camera Shake
in Computer Graphics Forum
![publication icon](/resources/img/placeholder-60x60.png)
Zhang X
(2018)
MyHealthAvatar lifestyle management support for cancer patients.
in Ecancermedicalscience