Authors:
Reem Abdel-Salam
;
Reem Gody
;
Mariam Maher
;
Hagar Hosny
and
Ahmed S. Kaseb
Affiliation:
Computer Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt
Keyword(s):
Multimedia, AI, NLP, Storytelling, Scene Generation, Story Generation, Information Extraction.
Abstract:
Stories are an effective and entertaining way of teaching children about real-life experiences in an engaging way. Although many children’s stories are supplemented with graphical illustrations, having animated 3D video illustrations can effectively boost the learning process, especially for visual learners. However, producing animated 3D videos is a hard, expensive, and time-consuming process, so there is a need to automate this process. In this paper, we introduce AnimaChaotic, a story visualization system designed to automatically convert children’s short stories to animated 3D videos by leveraging Artificial Intelligence (AI) and computer graphics. Our Natural Language Processing (NLP) pipeline extracts visualizable information from the story such as actors and actions. Then, our object positioning algorithm determines the initial positions of the objects in the scene. Finally, the system animates the scene using different techniques including AI behaviors. A quantitative analysi
s of our system demonstrates a high precision and recall in extracting visualizable information. It also shows that our system outperforms existing solutions in terms of static scene generation. A qualitative analysis of the system shows that its output is visually acceptable and outperforms similar solutions.
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