基于多自主智能体的群体动画创作

群体动画一直是计算机动画界一个具有挑战性的研究方向，提出了一个基于多自主智能体的群体动画创作框架：群体中的各角色作为自主智能体，能感知环境信息，产生意图，规划行为，最后通过运动系统产生运动来完成行为和实现意图，与传统的角色运动生成机理不同，首先采用运动捕获系统建立基本运动库，然后通过运动编辑技术对基本运动进行处理以最终得到角色运动，应用本技术，动画师只需“拍摄”角色群体的运动就能创作群体动画，极大地提高了制作效率。

Group Animation Based on Multiple Autonomous Agents

Group animation is a continuous challenge in computer animation. In this paper, a group animation framework based on multiple autonomous agents. Each animated character in a group is modeled as an autonomous agent, which can perceive information from the virtual environment, generate appropriate intentions, manage rational behaviors, and create motions to realize the intention. Contrary to traditional intelligent animated character techniques, motions for the animated character are generated using a motion capture data, instead of modeling the complex motion generation mechanism. First a fundamental motion library is built using motion capture system, then appropriate fundamental motions are selected from the fundamental motion library, and desired motions are synthesized from these fundamental ones. The animated characters manage their movement autonomically in the virtual environment. To produce the required group animation, animators only need to specify some simple information and record the useful group motion. The experiment shows the effectiveness of this framework.