Research map / 3D vision / Depth and stereo
A Direct Least-Squares Solution to the PnP Problem With Unknown Focal Length
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Build the least-squares objective directly from the imaging equation so all correspondences contribute equally | DLSPnPf · Synthetic PnPf | rotation, translation, and focal-length error | Helped |
| Use a noniterative solution instead of iterative refinement | DLSPnPf versus UPnPf+GN and GPnPf+GN · Synthetic PnPf, including near-planar and planar configurations | estimation accuracy | Helped |
| Use the direct least-squares solver rather than the minimal 4-point solvers | PnPf · Minimal 4-point case | rotation and focal-length error | Helped |
| Use the Grӧbner basis solver instead of the polynomial eigenvalue solver | DLSPnPf · Synthetic numerical-precision tests | focal-length relative error | Hurt |
| Use the Grӧbner basis solver instead of the polynomial eigenvalue solver | DLSPnPf · Synthetic runtime tests | running time | Helped |
| Increase the number of 3D-to-2D correspondences | PnPf estimation · Synthetic nonplanar, near-planar, and planar point configurations | rotation, translation, and focal-length error | Helped |
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