Virtual Environment Positioning Utilizing Play-Script Spatiotemporal Reasoning

Automatically staging characters in order to facilitate the performance and blocking of a scene in a virtual environment is a difficult task today. There is only a limited set of techniques used in practice. Some general methods include Behavior Markup Language (BML) and motion capture replay (the most popular); however they require either detailed technical knowledge or are not adaptable to different environmental configurations. In this work, we block and perform scenes with synthetic actors utilizing only a text-based, standard play-script as the primary input to the positioning of these characters in an environment. Using natural language processing techniques, we extract the annotated movements from the script, then add additional movements and adjustments from our rules engine built with theater, stage performance, and human interaction spatiotemporal relationships. In addition, we incorporate force-directed graph algorithms to adjust positions of the artificially intelligent (AI)-driven characters based on human-controlled character movements for interaction. These techniques have been quantitatively and qualitatively evaluated, revealing both similar blocking, and indistinguishably good performances from a human's perspective, when compared to an actual human performance.