Minimum Spanning Tree Pose Estimation

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Minimum Spanning Tree Pose Estimation
The extrinsic camera parameters from video stream images can be accurately estimated by tracking features through the image sequence and using these features to compute parameter estimates. The poses for long video sequences have been estimated in this manner. However, the poses of large sets of still images cannot be estimated using the same strategy because wide-baseline correspondences are not as robust as narrow-baseline feature tracks. Moreover, video pose estimation requires a linear or hierarchically-linear ordering on the images to be calibrated, reducing the image matches to the neighboring video frames. We propose a novel generalization to the linear ordering requirement of video pose estimation by computing the Minimum Spanning Tree of the camera adjacency graph and using the tree hierarchy to determine the calibration order for a set of input images. We validate the pose accuracy using an error metric that is functionally independent of the estimation process. Because we d...
Kevin L. Steele, Parris K. Egbert
Added 10 Jun 2010
Updated 10 Jun 2010
Type Conference
Year 2006
Where 3DPVT
Authors Kevin L. Steele, Parris K. Egbert
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