Posing 3D Models from Drawing

Inferring the 3D pose of a character from a drawing is a complex and under-constrained problem. Solving it may help automate various parts of an animation production pipeline such as pre-visualisation. In this paper, a novel way of inferring the 3D pose from a monocular 2D sketch is proposed. The proposed method does not make any external assumptions about the model, allowing it to be used on different types of characters. The inference of the 3D pose is formulated as an optimisation problem and a parallel variation of the Particle Swarm Optimisation algorithm called PARAC-LOAPSO is utilised for searching the minimum. Testing in isolation as well as part of a larger scene, the presented method is evaluated by posing a lamp, a horse and a human character. The results show that this method is robust, highly scalable and is able to be extended to various types of models

3D storyboarding for modern animation.

Animation is now a classic medium that has been practiced for over a century. While Disney arguably made it mainstream with some hand-drawn classics, today’s industry is focused on Three-Dimensional (3D) animation. In modern 3D animation productions, there have been significant leaps in terms of optimising, automating and removing manual tasks. This has allowed the artistic vision to be realised within time and budget and empowered artists to do things that in the past would be technically more difficult. However, most existing research is focused on specific tasks or processes rather than the pipeline itself. Moreover, it is mostly focused on elements of the animation production phase, such as modelling, animating and rendering. As a result, pre-production parts like storyboarding are still done in the traditional way, often drawn by hand. Because of this disparity between the old and the new, the transition from storyboarding to 3D is prone to errors. 3D storyboarding is an attempt to adapt the pre-production phase of modern animation productions. By allowing storyboard artists access to simple but scale-accurate 3D models early on, drawing times as well as transition times between pre-production and production can be reduced. However, 3D storyboarding comes with its own shortcomings. By analysing existing pipelines, points of potential improvement are identified. Motivating research from these points, alternative workflows, automated methods and novel ideas that can be combined to make 3D animation pipelines more efficient are presented. The research detailed in this thesis focuses on the area between pre-production and production. A pipeline is presented that consists of a portfolio of projects that aim to: • Generate place-holder character assets from a drawn character line-up • Create project files with scene and shot breakdowns using screenplays • Empower non-experts to pose 3D characters using Microsoft Kinect • Pose 3D assets automatically by using 2D drawings as input