Abstract
Uncalibrated reconstruction of a scene is desired in many practical applications of computer vision. However, using a single camera with unconstrained motion and unknown parameters, a true Euclidean three-dimensional (3-D) model of the scene cannot be reconstructed. In this paper, we present a method for true Euclidean 3-D reconstruction using an active vision system consisting of a pattern projector and a camera. When the intrinsic and extrinsic parameters of the camera are changed during the reconstruction, they can be self-calibrated and the real 3-D model of the scene can then be reconstructed. The parameters of the projector are precalibrated and are kept constant during the reconstruction process. This allows the configuration of the vision system to be varied during a reconstruction task, which increases its self-adaptability to the environment or scene structure in which it is to work.
| Original language | English |
|---|---|
| Pages (from-to) | 15-25 |
| Journal | IEEE Transactions on Robotics and Automation |
| Volume | 20 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Feb 2004 |
Research Keywords
- Homography
- Self-calibration
- Three-dimensional (3-D) reconstruction
- Uncalibrated reconstruction
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