Year: 2014
Type: article
Abstract: In this work, we discuss and evaluate the reliability of first order uncertainty propagation results in context of \nspherical Structure from Motion, concluding that they are not valid without restrictions, but depend on the choice of \nthe objective function. We furthermore show that the choice of the widely used geodesic error as objective function \nfor a reprojection error optimization leads to disproportional pose uncertainty results of spherical cameras. \nThis work identifies and outlines alternative objective functions to bypass those obstacles by deducing Jacobian \nmatrices according to the chosen objective functions with subsequent conduction of first order uncertainty propagation. \nWe evaluate the performance of the different objective functions in different optimization scenarios and \nshow that best results for uncertainty propagation are obtained using the Euclidean distance to measure deviations \nof image points on the spherical image.
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3214232930