Name
Title | ||
|---|---|---|
Combining Semantic and Geometric Features for Object Class Segmentation of Indoor Scenes |
Abstract | ||
|---|---|---|
Scene understanding is a necessary prerequisite for robots acting autonomously in complex environments. Low-cost RGB-D cameras such as Microsoft Kinect enabled new methods for analyzing indoor scenes and are now ubiquitously used in indoor robotics. We investigate strategies for efficient pixelwise object class labeling of indoor scenes that combine both pretrained semantic features transferred fr... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LRA.2016.2532927 | IEEE Robotics and Automation Letters |
Keywords | Field | DocType |
Semantics,Feature extraction,Color,Labeling,Image segmentation,Training,Cameras | Computer vision,Pattern recognition,Segmentation,Computer science,Image segmentation,Feature extraction,RGB color model,Artificial intelligence,Deep learning,Robot,Feature learning,Color image | Journal |
Volume | Issue | ISSN |
2 | 1 | 2377-3766 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farzad Husain | 1 | 25 | 2.75 |
| Hannes Schulz | 2 | 55 | 10.82 |
| Babette Dellen | 3 | 235 | 16.51 |
| Carme Torras | 4 | 1155 | 115.66 |
| Sven Behnke | 5 | 1672 | 181.84 |