Adaptive animation generation using web content mining

Creating 3D animation is a labor-intensive and time-consuming process requiring designers to learn and utilize a complex combination of menus, dialog boxes, buttons and manipulation interfaces for a given stand-alone animation design software. On the other hand, conceptual simplicity and naturalness of visualizing imaginations from lingual descriptions motivates researchers for developing automatic animation generation systems using natural language interfaces. In this research, we introduce an interactive and adaptive animation generation system that utilizes data-driven techniques to extract the required common-sense and domain-specific knowledge from web. This system is capable of creating 3D animation based on user's lingual commands. It uses the user interactions as a relevance feedback to learn the implicit design knowledge, correct the extracted knowledge, and manipulate the dynamics of the virtual world in an active and incremental manner. Moreover, system is designed based on a multi-agent methodology which provides it with distributed processing capabilities and cross-platform characteristics. In this paper, we will focus on information retrieval agent which is responsible for extracting numeric data utilized in object attributes, spatiotemporal relations, and environment dynamics using web mining techniques.