Image-based Authoring of Herd Animations - Archive ouverte HAL Access content directly
Journal Articles Computer Animation and Virtual Worlds Year : 2019

Image-based Authoring of Herd Animations

(1) , (2) , (1) , (1)
1
2

Abstract

Animating herds of animals while achieving both convincing global shapes and plausible distributions within the herd is difficult using simulation methods. In this work, we allow users to rely on photos of real herds, which are widely available, for key-framing their animation. More precisely, we learn global and local distribution features in each photo of the input set (which may depict different numbers of animals) and transfer them to the group of animals to be animated, thanks to a new statistical learning method enabling to analyse distributions of ellipses, as well as their density and orientation fields. The animated herd reconstructs the desired distribution at each key-frame while avoiding obstacles. As our results show, our method offers both high level user control and help towards realism, enabling to easily author herd animations.
Fichier principal
Vignette du fichier
main.pdf (11.51 Mo) Télécharger le fichier
Vignette du fichier
teaser.png (2.88 Mo) Télécharger le fichier
Vignette du fichier
herd_demo_1080p.mp4 (95.26 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Format : Figure, Image
Loading...

Dates and versions

hal-02127824 , version 1 (17-05-2019)

Identifiers

Cite

Pierre Ecormier-Nocca, Julien Pettré, Pooran Memari, Marie-Paule Cani. Image-based Authoring of Herd Animations. Computer Animation and Virtual Worlds, 2019, 30 (3-4), pp.1-11. ⟨10.1002/cav.1903⟩. ⟨hal-02127824⟩
334 View
335 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More