Gouvatsos, AlexandrosXiao, ZhidongMarsden, NeilZhang, Jian J.John Keyser and Young J. Kim and Peter Wonka2014-12-162014-12-162014978-3-905674-73-6https://doi.org/10.2312/pgs.20141264Inferring the 3D pose of a character from a drawing is a non-trivial 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 3D pose inference 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 and a horse character. The results show that this method is robust and is able to be extended to various types of models.I.2.8 [Artificial Intelligence]Problem SolvingControl MethodsSearchHeuristic methodsI.2.10 [Artificial Intelligence]Vision and Scene UnderstandingShapeI.3.7 [Computer Graphics]Three Dimensional Graphics and RealismAnimationI.4.9 [Image Processing and Computer Vision]Applications