群体动画一直是电影制作领域具有挑战性的研究热点. 针对目前电影混战场景数字化仿真存在的运动模式单一、真实感较差、工作量大等问题, 提出基于多自主智能体的电影混战群体仿真方法. 首先, 根据场景规模和角度智能划分作战区域, 并建立相应的局部KD树(K-dimension tree); 然后, 在个体角色具有视觉感知、避障、逃避、智能调用动作数据等行为的基础上, 对混战场景中的群体角色进行智能控制, 实现群体聚集、追随、智能搜索攻击目标等行为. 实验结果表明, 该方法是可行的, 能够较好地模拟电影混战场景中复杂的多角色智能运动, 且具有较高的逼真度.

Group animation has been a challenging research topic in the field of film production. In view of the fact that current digital emulation simulation of the movie battle scene is flawed with the problems of single motion mode, poor authenticity and heavy workload, this paper proposes a method of group simulation for film melee scenes based on the multiple autonomous agents. First, the area of operation is intelligently divided according to the scale and angle of the scene, and the corresponding local KD tree is established. Then, on the basis of visual perception, obstacle avoidance, evasion, and intelligent invoking of action data, the group roles in the melee scenes are intelligently controlled, achieving group behaviors such as group follow-up, grouping, the intelligent search target, and so on. The experimental results show that the proposed methodis feasible, and that it could simulate the multi-role intelligent movement of the complex film melee scenes well with high fidelity.