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Minimizing probable collision pairs searched in interactive animation authoring

机译:最小化交互式动画创作中搜索的可能碰撞对

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Animation authoring involves an author's interaction with a scene, resulting in varying scene complexity for a given animation sequence. In such a varying environment, detection and prediction of collision in minimal time and with high accuracy is a challenge. This paper proposes using the bounding volume-based space subdivision mechanism to reduce search space for an object pair collision search. This data structure is enhanced using a direction-based spatial hash table, which predicts collision between static and dynamic objects. These techniques are shown to work in conjunction with existing search space reduction methods. The event of collision is accurately detected using known methods, such as kinetic data structures. Simulation results show that for a scene with 10000 objects with varying dynamic objects (10%-90%), the method finds probable collision-pairs with 95%-99% accuracy.
机译:动画创作涉及作者与场景的交互,从而导致给定动画序列的场景复杂度有所变化。在这种变化的环境中,在最短的时间内以高精度检测和预测碰撞是一个挑战。本文提出使用基于边界体积的空间细分机制来减少对象对碰撞搜索的搜索空间。使用基于方向的空间哈希表可增强此数据结构,该表可预测静态对象与动态对象之间的冲突。这些技术显示与现有的搜索空间缩减方法结合使用。使用已知方法(例如动力学数据结构)可以准确地检测到碰撞事件。仿真结果表明,对于具有10000个对象且动态对象变化(10%-90%)的场景,该方法可以找到95%-99%的可能碰撞对。

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