摘要
基于移动立方体(marching cubes,MC)算法,考虑到现实条件下观测数据的不完整性,提出一个方便模式识别研究的可伸缩三维数据场模型.该模型混合MC算法和分区域处理方法,考虑了多角度观测对场域及目标的影响,描述了三维数据场对模式识别的作用.场域建立的实践表明,利用多观测点互相补充的方法改进了MC算法,提高了运行效率.
According to marching cubes（MC）algorithm,considering the incompleteness observation data in practical conditions,a convenient scalable 3D data field model is proposed for study on pattern recognition.The model is a mixture of MC algorithm and sub regional treatment,considered a key influence of multi-angle observation which means on the field and the goal.Then the effect to pattern recognition in 3D data field is described.In the process of the data field,it complements each other by using the method of multiple observation points for the improvement and operation efficiency of MC algorithm.
出处
《江苏师范大学学报（自然科学版）》
CAS
2014年第4期59-60,74,共3页
Journal of Jiangsu Normal University：Natural Science Edition
基金
国家863计划资助项目(2007AA11Z249)
关键词
移动立方体算法
数据场
三维可视化
模式识别
marching cubes（MC）algorithm
data field
3D visualization
pattern recognition
