Discontinuous and Smooth Depth Completion With Binary Anisotropic Diffusion Tensor
| Autor: | Menandro Roxas, Jun Shimamura, Shingo Ando, Takeshi Oishi, Yasuhiro Yao, Ryoichi Ishikawa |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Control and Optimization Computer science Anisotropic diffusion Computer Vision and Pattern Recognition (cs.CV) Nearest neighbor search Computer Science - Computer Vision and Pattern Recognition Biomedical Engineering Point cloud 02 engineering and technology Computer Science - Robotics 020901 industrial engineering & automation Artificial Intelligence Depth map 0202 electrical engineering electronic engineering information engineering Tensor ComputingMethodologies_COMPUTERGRAPHICS Mechanical Engineering Computer Science Applications Human-Computer Interaction Control and Systems Engineering Piecewise 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Robotics (cs.RO) Algorithm |
| Zdroj: | IEEE Robotics and Automation Letters. 5:5128-5135 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2020.3005890 |
| Popis: | We propose an unsupervised real-time dense depth completion from a sparse depth map guided by a single image. Our method generates a smooth depth map while preserving discontinuity between different objects. Our key idea is a Binary Anisotropic Diffusion Tensor (B-ADT) which can completely eliminate smoothness constraint at intended positions and directions by applying it to variational regularization. We also propose an Image-guided Nearest Neighbor Search (IGNNS) to derive a piecewise constant depth map which is used for B-ADT derivation and in the data term of the variational energy. Our experiments show that our method can outperform previous unsupervised and semi-supervised depth completion methods in terms of accuracy. Moreover, since our resulting depth map preserves the discontinuity between objects, the result can be converted to a visually plausible point cloud. This is remarkable since previous methods generate unnatural surface-like artifacts between discontinuous objects. Comment: 8 pages 6 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|