Name
Abstract | ||
|---|---|---|
With the improvements in sensor technologies and image processing algorithms, computer vision has become a major tool for robots to recognize and gauge their surroundings. For instance, the Kinect sensor can be used as an excellent depth camera for indoor navigation. However, there exist situations that need recognition and spatial interpretation of the environment using limited hardware resources. The Kinect is not suitable for outdoor use while LIDAR is too large and expensive to be installed on an autonomous miniature surveillance drone. Therefore, the use of a single camera is the only feasible option for many embedded applications. Hence, this paper examines different Structure from Motion (SfM) implementations, and focus on methods that require only one camera to perform an efficient 3D mapping of a scene. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/EIT.2015.7293365 | 2015 IEEE International Conference on Electro/Information Technology (EIT) |
Keywords | Field | DocType |
motion based single camera 3D mapping,sensor technologies,image processing algorithms,computer vision,Kinect sensor,depth camera,indoor navigation,structure from motion,SfM,3D scene mapping | Structure from motion,Computer vision,Camera interface,Computer science,Camera auto-calibration,Smart camera,Feature extraction,Camera resectioning,Artificial intelligence,Digital image processing,Robot | Conference |
ISSN | Citations | PageRank |
2154-0357 | 2 | 0.41 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guojun Yang | 1 | 4 | 2.83 |
| Zhen Zhou | 2 | 2 | 0.41 |
| Thomas Gonnot | 3 | 7 | 4.17 |
| Jafar Saniie | 4 | 152 | 47.55 |