Motion Compression using Principal Geodesics Analysis - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Poster Communications Year : 2008

Motion Compression using Principal Geodesics Analysis

Abstract

We present a novel, lossy compression method for human motion data that exploits both temporal and spatial coherence. We first build a compact skeleton pose model from a single motion using Principal Geodesic Analysis (PGA). The key idea is to perform compression by only storing the model parameters along with the end-joints and root joint trajectories in the output data. The input data are recovered by optimizing PGA variables to match end-effectors positions in an inverse kinematics approach. Our experimental results show that considerable compression rates can be obtained using our method, with few reconstruction and perceptual errors. Thanks to the embedding of the pose model, our system can also be suitable for motion editing purposes.
Fichier principal
Vignette du fichier
tournier08.pdf (61.4 Ko) Télécharger le fichier
Vignette du fichier
85_12_9-9-15-4456.jpg (50.11 Ko) Télécharger le fichier
poster.pdf (626.31 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Format : Figure, Image
Format : Other
Loading...

Dates and versions

inria-00590253 , version 1 (03-05-2011)

Identifiers

  • HAL Id : inria-00590253 , version 1

Cite

Maxime Tournier, Lionel Reveret, Xiaomao Wu, Nicolas Courty, Élise Arnaud. Motion Compression using Principal Geodesics Analysis. SCA '08 - ACM-SIGGRAPH/Eurographics Symposium on Computer Animation, Jul 2008, Dublin, Ireland. 2008. ⟨inria-00590253⟩
294 View
240 Download

Share

Gmail Facebook X LinkedIn More