A framework for image-based asset generation and animation

Abstract

Creating digital animatable models of real-world objects and characters is important for many applications, ranging from highly expensive movie productions to low-cost real-time applications like computer games and augmented reality. However, achieving real photorealism with convincing appearance and deformation behavior requires sophisticated capturing, elaborate manual modeling and time-consuming simulation. This can only be achieved in well funded film productions, while in low-cost applications, animated objects usually lack visual quality. In this paper, we present a new framework for image-based animatable asset generation which avoids these time-consuming processes both in the modeling and the simulation stage. Real-time photo-realistic animation is enabled by the use of captured images and shifting computational complexity to an a-priori training phase. Our paper covers the complete pipeline of content creation, asset generation and representation, and a real-time animation and rendering implementation.

DOI: 10.1109/ICIP.2015.7351141

Extracted Key Phrases

6 Figures and Tables

Cite this paper

@article{Furch2015AFF, title={A framework for image-based asset generation and animation}, author={Johannes Furch and Anna Hilsmann and Peter Eisert}, journal={2015 IEEE International Conference on Image Processing (ICIP)}, year={2015}, pages={1950-1954} }