Tagged / computer animation

New publication by NCCA: 4D Cubism as a novel artistic technology

“IEEE Computer Graphics and Applications”, an influential magazine with a wide readership in both academia and industry, has just published the paper “4D Cubism: Modeling, Animation and Fabrication of Artistic Shapes”.

This multidisciplinary paper proposing a novel technology on the edge of art and science has been written by a team from the National Centre for Computer Animation (NCCA) of the Faculty of Media and Communication. The authors are Quentin Corker-Marin, Prof Alexander Pasko, and Dr Valery Adzhiev.

The paper has a non-trivial history. Initially, there was an UG student project (“Innovations” unit, “Computer Visualisation and Animation” course, Level 6) that was submitted as a Poster to the ACM SIGGRAPH 2017 conference in Los Angeles. As it was reported in the Research Blog in September 2017, Quentin was awarded there the second prize in the prestigious ACM Student Research Competition sponsored by Microsoft. Then a full-scale paper was submitted to the top magazine, and after successful peer-reviewing it was accepted and published. As to Quentin, in the end of 2017 he graduated from NCCA with a first class honours degree in computer visualisation and animation and works now in London as a 3D Artist for an award-winning production company Glassworks.

References

BU Briefing – Exploiting temporal stability and low-rank structure for motion capture data refinement

Our BU briefing papers are designed to make our research outputs accessible and easily digestible so that our research findings can quickly be applied – whether to society, culture, public policy, services, the environment or to improve quality of life. They have been created to highlight research findings and their potential impact within their field. 


In recent years, motion capture data (mocap) have been widely used in computer games, film production and sport sciences. The great success of animated and animation enhanced feature films, such as Avatar, provide compelling evidence for the values of mocap techniques. However, even with the most expensive commercial mocap systems, there are still instances where noise and missing data are inevitable.

This paper examines the motion refinement problem and presents an effective framework to solve it, demonstrated by extensive experiments on both synthetic and real data. The experiment shows that the proposed method outperforms all competitors not only in predicting missing values but also in de-noising most of the time.

Click here to read the briefing paper.


For more information about the research, contact Dr Xiaosong Yang at xyang@bournemouth.ac.uk or Professor Jian Jun Zhang at jzhang@bournemouth.ac.uk.
To find out how your research output could be turned into a BU Briefing, contact research@bournemouth.ac.uk.