Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
