Virtual Environments: Graphtracker: A topology projection invariant optical tracker
Computers and Graphics
Technical Section: A simulator-based approach to evaluating optical trackers
Computers and Graphics
Pose estimation from multiple cameras based on Sylvester's equation
Computer Vision and Image Understanding
Spherical approximation for multiple cameras in motion estimation: Its applicability and advantages
Computer Vision and Image Understanding
A framework for performance evaluation of model-based optical trackers
EGVE'08 Proceedings of the 14th Eurographics conference on Virtual Environments
| Hi-index | 0.00 |
Pose estimation of a multiple camera system (MCS) is usually achieved by either solving the PnP problem or finding the least-squared-error rigid transformation between two 3D point sets. These methods employ partial information of an MCS, in which only a small number of features in one or two cameras can be utilized. To overcome this limitation, we propose a new pose estimation method for an MCS that uses complete information of an MCS. In our method, we treat the MCS as a single generalized camera [A general imaging model and a method for finding its parameters][Using many cameras as one] and formulate this problem in a least-squared manner. An iterative algorithm is proposed for solving the least-squared problem. From the experimental results, it shows that the proposed method is accurate for pose estimation of MCS.