Part-level 3-D object classification with improved interpretation tree

For classifying unknown 3-D objects into a set of predetermined object classes, a part-level object classification method based on the improved interpretation tree is presented. The part-level representation is implemented, which enables a more compact shape description of 3-D objects. The proposed classification method consists of two key processing stages： the improved constrained search on an interpretation tree and the following shape similarity measure computation. By the classification method, both whole match and partial match with shape similarity ranks are achieved; especially, focus match can be accomplished, where different key parts may be labeled and all the matched models containing corresponding key parts may be obtained. A series of experiments show the effectiveness of the presented 3-D object classification method.

双摄像机相位测量轮廓术系统标定与数据融合

在将两个摄像机对同一坐标系(全局坐标系)标定的基础上,提出了距离数据及纹理的融合方法。以调制度为模板确定摄像机视线重叠区和数据空洞,在全局坐标中摄像机视线重叠区内根据单位面积采样点数序号最接近原则选取一定尺寸的区域作为数据拼接区。并且考虑在重叠区内一方数据有空洞时的补洞方法,将空洞边界相似放大后,新边界和原边界构成的重叠区域作为数据拼接区。在数据拼接区内将两边的数据以到拼接区中心线距离为权重进行加权平均,实现了数据平滑过渡。实验表明该方法是有效的,为数据融合提供了新途径。