Name
Title | ||
|---|---|---|
Aggregation of Rich Depth-Aware Features in a Modified Stacked Generalization Model for Single Image Depth Estimation |
Abstract | ||
|---|---|---|
Estimating scene depth from a single monocular image is a crucial component in computer vision tasks, enabling many further applications such as robot vision, 3-D modeling, and above all, 2-D to 3-D image/video conversion. Since there are an infinite number of possible world scenes, that can produce a unique image, single image depth estimation is a highly challenging task. This paper tackles such an ambiguous problem by using the merits of both global and local information (structures) of a scene. To this end, we formulate single image depth estimation as a regression problem via (on) rich depth related features which describe effective monocular cues. Exploiting the relationship between these image features and depth values is adopted via a learning model which is inspired by modified stacked generalization scheme. The experiments demonstrate competitive results compared with existing data-driven approaches in both quantitative and qualitative analysis with a remarkably simpler approach than previous works. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TCSVT.2018.2808682 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | DocType | Volume |
Estimation,Three-dimensional displays,Training,Two dimensional displays,Semantics,Solid modeling,Feature extraction | Journal | 29 |
Issue | ISSN | Citations |
3 | 1051-8215 | 4 |
PageRank | References | Authors |
0.48 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hoda Mohaghegh | 1 | 4 | 0.48 |
| Nader Karimi | 2 | 145 | 32.75 |
| S. M. R. Soroushmehr | 3 | 71 | 21.08 |
| Shadrokh Samavi | 4 | 233 | 38.99 |
| Kayvan Najarian | 5 | 262 | 59.53 |