Name
Title | ||
|---|---|---|
Robust non-rigid point set registration method based on asymmetric Gaussian and structural feature. |
Abstract | ||
|---|---|---|
Point set registration is a fundamental problem in many domains of computer vision. In previous work on the registration, the point sets are often represented using Gaussian mixture models and the registration process is represented as a form of a probabilistic solution. For non-rigid point set registration, however, the asymmetric Gaussian (AG) model can capture spatially asymmetric distributions... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-cvi.2017.0550 | IET Computer Vision |
Keywords | Field | DocType |
computer vision,Gaussian distribution,image registration,image representation,mixture models,probability | Point set registration,Probability density estimation,Pattern recognition,Gaussian,Artificial intelligence,Point set,Probabilistic logic,Shape context,Mathematics,Mixture model | Journal |
Volume | Issue | ISSN |
12 | 6 | 1751-9632 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Dou | 1 | 0 | 0.34 |
| Dongmei Niu | 2 | 2 | 6.44 |
| Zhiquan Feng | 3 | 36 | 13.73 |
| Xiuyang Zhao | 4 | 73 | 13.60 |