Emotion challenge: building a new photoreal facial performance pipeline for games
Proceedings of the ACM SIGGRAPH Digital Production Symposium(2017)
摘要
In recent years the expected standard for facial animation and character performance in AAA video games has dramatically increased. The use of photogrammetric capture techniques for actor-likeness acquisition, coupled with video-based facial capture and solving methods, has improved quality across the industry. However, due to variability across project pipelines, increased per-project scope for performance capture, and a reliance on external vendors, it is often challenging to maintain visual consistency from project to project, and even from character to character within a single project. Given these factors, we identified the need for a unified, robust, and scalable pipeline for actor likeness acquisition, character art, performance capture, and character animation.
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