Virtual 3D camera composition from frame constraints
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Artificial Intelligence
An Intent-Driven Planner for Multi-Agent Story Generation
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Real-time cinematic camera control for interactive narratives
Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology
Comparing cognitive and computational models of narrative structure
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A discourse planning approach to cinematic camera control for narratives in virtual environments
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
TALE-SPIN, an interactive program that writes stories
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 1
Declarative camera control for automatic cinematography
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Virtual camera planning: a survey
SG'05 Proceedings of the 5th international conference on Smart Graphics
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Computational storytelling systems have mainly focused on the construction and evaluation of textual discourse for communicating stories. Few intelligent camera systems have been built in 3D environments for effective visual communication of stories. The evaluation of effectiveness of these systems, if any, has focused mainly on the run-time performance of the camera placement algorithms. The purpose of this paper is to present a systematic cognitive-based evaluation methodology to compare effects of different cinematic visualization strategies on viewer comprehension of stories. In particular, an evaluation of automatically generated visualizations from Darshak, a cinematic planning system, against different hand-generated visualization strategies is presented. The methodology used in the empirical evaluation is based on QUEST, a cognitive framework for question-answering in the context of stories, that provides validated predictors for measuring story coherence in readers. Data collected from viewers, who watch the same story renedered with three different visualization strategies, is compared with QUEST's predictor metrics. Initial data analysis establishes significant effect on choice of visualization strategy on story comprehension. It further shows a significant effect of visualization strategy selected by Darshak on viewers' measured story coherence.