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Swarm-Based Identification of Animation Key Points from 2D-medialness Maps

Aparajeya, Prashant; Leymarie, Frederic Fol and al-Rifaie, Mohammad Majid. 2019. Swarm-Based Identification of Animation Key Points from 2D-medialness Maps. In: Anikó Ekárt; Antonios Liapis and María Luz Castro Pena, eds. Computational Intelligence in Music, Sound, Art and Design. 11453 Cham, Switzerland: Springer, pp. 69-83. ISBN 9783030166663 [Book Section]

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Abstract or Description

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:

Book Section

Identification Number (DOI):

https://doi.org/10.1007/978-3-030-16667-0_5

Additional Information:

Best paper award at EvoMusart 2019, in Leipzig, Germany.

Keywords:

Line of action, Medialness, Dispersive flies optimisation, Swarms, Dominant points, Animation

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
February 2019Accepted
April 2019Published

Item ID:

26330

Date Deposited:

15 May 2019 13:32

Last Modified:

15 May 2019 13:34

URI:

http://research.gold.ac.uk/id/eprint/26330

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