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作 者:黄松柏[1]
机构地区:[1]北京化工大学信息科学与技术学院,北京100029
出 处:《北京石油化工学院学报》2011年第1期16-21,共6页Journal of Beijing Institute of Petrochemical Technology
基 金:北京市科技发展计划项目;项目号:2008
摘 要:在虚拟场景中普遍采用基于OBB包围盒的碰撞检测技术,然而传统算法对于大数据量模型的检测仍然效率不高,难以保证实时性。在分析了OBB及其改进算法的基础上,采用改进的OBB中心计算方法,使包围盒能够更紧密的包围模型,提高碰撞检测的准确性和时间效率。在碰撞检测过程中动态地建立OBB层次结构,减少了时间复杂度和空间复杂度。分析和实验结果证明,改进后的算法在处理一般曲面模型尤其是大数据曲面模型时,碰撞检测的稳定性和效率都有明显提高。The collision detection algorithm based on the orientation bounding box(OBB) is widely used in the virtual environment,but the traditional algorithm has low efficiency while processing the large surface models,and can't guarantees the real-time performance.An improved algorithm was developed based on a new method that computes the centre of the orientation bounding box,which ensures the bounding box enclosing the model more closely and improves the accuracy and time efficiency of collision detection.By using the algorithm,the OBB hierarchy tree can be built dynamically while collision detecting,and thus the time cost and memory cost could be decreased.The theoretical analysis and experiments prove that the improved algorithm enhances the stability and efficiency obviously while processing the collision detection of large surface models.
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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