基于Zernike矩的三维目标多视点特性视图建模

目标的模型化是三维目标识别的一个重要环节。由于从多视点特征法建立的模型能够避免从二维图像中恢复目标的三维结构．在三维目标识别中应用比较广泛。使用镶嵌式多面体分割视觉空间以得到三维目标的多视点投影图像，采用较小的镶嵌单元尺寸以完备地描述目标各种姿态的信息。Zernike矩具有旋转不变性，并能够方便地由各阶矩重建图像。计算多面体各个单元的投影图像的Zernike矩．所需的矩的最高阶次由重建图像与原图像的差别确定，通过聚类方式合并那些图像的矩变化很小的投影对应的几个小单元．每个新单元可以提取一幅特性视图．实现较小数目的多视点特性视图的建模。实验证明了这种方法的可行性。

Multi-view modeling of 3-D target based on Zernike moments

Modeling is an important step in 3-D target recognition. Avoiding the recovery of 3-D obje- ct, multi-view modeling is used widely in 3-D object modeling. Multiple 2-D views are obtained by proje- cting a tessellated regular polyhedron onto the viewing sphere.In order to describe all shape and pose info- rmation, a fine partition of the viewing sphere is necessary,which leads to computation complexity. Zernike moments have a rotation invariant property. A method is used to decrease the number of 2-D projections view by extracting the Zernike moments of each 2-D view, whose max order is decided by the difference between the original image and the reconstruction one.Those partitions with Zernike moments of correspon- ding views are similar are merged and a characteristic view is obtained for a new partition. Experimental results show the validity of the method.