位置:成果数据库 > 期刊 > 期刊详情页
基于距离直方图的最优视点选择
  • 期刊名称:计算机辅助设计与图形学学报
  • 时间:0
  • 页码:1515-1521
  • 语言:中文
  • 分类:O174.12[理学—数学;理学—基础数学] TN957.5[电子电信—信号与信息处理;电子电信—信息与通信工程]
  • 作者机构:[1]Key Laboratory of Intelligent Information Processing,Institute of Computing Technology Chinese Academy of Sciences, Beijing 100190, China, [2]University of Chinese Academy of Sciences, Beijing 100049, China, [3]School of Computer Science and Communication Engineering, China University of Petroleum, Qingdao 266555, China.
  • 相关基金:Partly Supported by NKBRPC(2004CB318006) and NNSFC (60873164 and 60533090).
  • 相关项目:基于三维深度数据与二维投影图像的人脸相似匹配与检索
中文摘要:

Non-rigid shape deformation without tearing or stretching is called isometry. There are many difficulties to research non-rigid shape in Euclidean space. Therefore, non-rigid shapes are firstly embedded into a none-Euclidean space. Spectral space is chosen in this paper. Then three descriptors are proposed based on three spectral distances. The existence of zero-eigenvalue has negative effects on computation of spectral distance. Therefore the spectral distance should be computed from the first non-zero-eigenvalue. Experiments show that spectral distance distributions are very effective to describe the non-rigid shapes.

英文摘要:

Non-rigid shape deformation without tearing or stretching is called isometry. There are many difficulties to research non-rigid shape in Euclidean space. Therefore, non-rigid shapes are firstly embedded into a none-Euclidean space. Spectral space is chosen in this paper. Then three descriptors are proposed based on three spectral distances. The existence of zero-eigenvalue has negative effects on computation of spectral distance, Therefore the spectral distance should be computed from the first non-zcro-eigenvalue. Experiments show that spectral distance distributions are very effective to describe the non-rigid shapes.

同期刊论文项目
期刊论文 92 会议论文 32 获奖 1 专利 15
同项目期刊论文