Point Pattern Matching Based on Manifold Embedding

摘要：

The problem of point pattern matching (PPM) is frequently encountered in computer vision, such as image registration and image matching. This paper investigates the manifold approaches to the probleM of point pattern matching, and proposes a manifold correspondence based on Locally Linear Embedding (LLE). Our method operates on embeddings of the two data sets in the manifold space so as to get embedding features, which is invariance to rotation, scaling and translation (RST). By comparing the manifold embeddings of the points, we locate correspondences. We evaluate the method on both synthetic and real-world data, and experimental results demonstrate its high accuracy and robust to outliers.

关键词： Point Pattern Matching (PPM) Manifold embedding Locally Linear Embedding (LLE) Non-rigid transformation

作者: Weidong Yan Zheng Tian Jinhuan Wen Lulu Pan

作者单位: School of Science, Northwestern Polytechnical University Xian, China School of Science, Northwestern Polytechnical University Xian, China State Key Laboratory of Remote

会议类型: 国际会议

会议名称: 2010 International Conference on Image Analysis and Signal Processing(2010 图像分析与信号处理国际会议 IASP 10)

会议地点: 厦门

会议语种:英文

页码: 502-506

在线出版日期: 2010-04-12（万方平台首次上网日期，不代表论文的发表时间）