Aparajeya, Prashant, Leymarie, Frederic Fol and Al-Rifaie, Mohammad Majid ORCID: https://orcid.org/0000-0002-1798-9615 (2019) Swarm-based identification of animation key points from 2D-medialness maps. In: EvoMUSART 2019: Computational Intelligence in Music, Sound, Art and Design. Lecture Notes in Computer Science (LNCS, volume 11453) . Springer International Publishing, Cham, pp. 69-83. ISBN 978-3-030-16666-3 (doi:10.1007/978-3-030-16667-0_5)

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Abstract

In this article we present the use of dispersive flies optimisation (DFO) for swarms of particles active on a medialness map — a 2D field representation of shape informed by perception studies. Optimising swarms activity permits to efficiently identify shape-based keypoints to automatically annotate movement and is capable of producing meaningful qualitative descriptions for animation applications. When taken together as a set, these keypoints represent the full body pose of a character in each processed frame. In addition, such keypoints can be used to embody the notion of the Line of Action (LoA), a well known classic technique from the Disney studios used to capture the overall pose of a character to be fleshed out. Keypoints along a medialness ridge are local peaks which are efficiently localised using DFO driven swarms. DFO is optimised in a way so that it does not need to scan every image pixel and always tend to converge at these peaks. A series of experimental trials on different animation characters in movement sequences confirms the promising performance of the optimiser over a simpler, currently-in-use brute-force approach.

Item Type:	Conference Proceedings
Title of Proceedings:	EvoMUSART 2019: Computational Intelligence in Music, Sound, Art and Design
Additional Information:	Also delivered on 25 April as a speech at 8th International Conference, EvoMUSART 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019.
Uncontrolled Keywords:	line of action, medialness, dispersive flies optimisation, swarm intelligence, dominant points, animation
Subjects:	Q Science > QA Mathematics
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Related URLs:	Organisation
Last Modified:	04 Mar 2022 13:06
URI:	http://gala.gre.ac.uk/id/eprint/23765

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