An optimization approach for extracting and encoding consistent maps in a shape collection
Abstract
We introduce a novel approach for computing high quality point-to-point maps among a collection of related shapes. The proposed approach takes as input a sparse set of imperfect initial maps between pairs of shapes and builds a compact data structure which implicitly encodes an improved set of maps between all pairs of shapes. These maps align well with point correspondences selected from initial maps; they map neighboring points to neighboring points; and they provide cycle-consistency, so that map compositions along cycles approximate the identity map.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 01, 2012
- Source ID
- 10.1145/2366145.2366186
Entities
People
- Adrian Butscher
- Guo-xin Zhang
- Leonidas J. Guibas
- Lin Gao
- Qi-xing Huang
- Shi-min Hu
Organizations
- Division of Computing and Communication Foundations
- Ministry of Science and Technology of the People's Republic of China
- National Natural Science Foundation of China
- National Science Foundation
- Office of Naval Research
- Stanford University
- Tsinghua University