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Gouvatsos, Alexandros; Xiao, Zhidong; Marsden, N.; Zhang, Jian J. (2015)
Languages: English
Types: Article
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.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • Received January 2015; revised N/A; accepted N/A
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