GeodesicEmbedding (GE): A High-Dimensional Embedding Approach for Fast Geodesic Distance Queries.
Qianwei XiaJuyong ZhangZheng FangJin LiMingyue ZhangBailin DengYing HePublished in: CoRR (2021)
Keyphrases
- geodesic distance
- high dimensional
- embedding space
- manifold learning
- euclidean space
- euclidean distance
- low dimensional
- shortest path
- dimensionality reduction
- query processing
- similarity search
- fisher information
- distance transform
- metric space
- data points
- geometric structure
- riemannian manifolds
- high dimensional data
- distance metric
- range queries
- multidimensional scaling
- nearest neighbor
- feature space
- dimension reduction
- multi dimensional
- shape analysis
- pattern recognition
- feature extraction
- computer vision