Inherent Ambiguities in Recovering 3-D Motion and Structure from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Analysis of Inherent Ambiguities in Recovering 3-D Motion from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
A critique of structure-from-motion algorithms
Computer Vision and Image Understanding
Optimal Structure from Motion: Local Ambiguities and Global Estimates
International Journal of Computer Vision
Characterizing Depth Distortion under Different Generic Motions
International Journal of Computer Vision
Understanding the Behavior of SFM Algorithms: A Geometric Approach
International Journal of Computer Vision
A New Structure-from-Motion Ambiguity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Depth distortion under calibration uncertainty
Computer Vision and Image Understanding
Behaviour of SFM algorithms with erroneous calibration
Computer Vision and Image Understanding
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This paper presents a theoretical analysis of the behavior of “Structure from Motion” (SFM) algorithms with respect to the errors in intrinsic parameters of the camera. We demonstrate both analytically and in simulation how uncertainty in the calibration parameters gets propagated to motion estimates. We studied the behavior of the estimation of the focus of expansion (FOE) in the case that the camera is well calibrated except that the focal length is estimated with error. The results suggest that the behavior of the bas-relief ambiguity is affected by the erroneous focal length. The amount of influence depends on the relative direction of the translation and rotation parameters of the camera, the field of view and scene depth. Simulation with synthetic data was conducted to support our findings.