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- Title
GPU-based Fast Motion Synthesis of Large Crowds Using Adaptive Multi-Joint Models.
- Authors
Sung, Mankyu; Kim, Yejin
- Abstract
This paper introduces a GPU (graphics processing unit)-based fast motion synthesis algorithm for a large crowd. The main parts of the algorithms were selecting the most appropriate joint model given adaptive screen-space occupancy of each character and synthesizing motions for the joint model with one or two input motion capture data. The different joint models had a character range from fine-detailed and fully-articulated ones to the most simplified ones. The motion synthesizer, running on a GPU, performed a series of motion blending for each joint of the characters in parallel. For better performance of the motion synthesizer, the GPU maintained a novel cache structure for given speed parameters. Using the high computation power of GPUs, the motion synthesizer could generate arbitrary speeds and orientations for the motions of a vast number of characters. Experiments showed that the proposed algorithm could animate more than 5000 characters in real-time on modest graphics acceleration cards.
- Subjects
GRAPHICS processing units; MOTION; MOTION capture (Human mechanics)
- Publication
Symmetry (20738994), 2019, Vol 11, Issue 3, p422
- ISSN
2073-8994
- Publication type
Article
- DOI
10.3390/sym11030422