Shen, ChunhuaLi, HongdongBrooks, Michael2015-12-08December 19780769534565http://hdl.handle.net/1885/34988Novel methods are proposed for self-calibrating a purerotating camera using semidefinite programming (SDP). Key to the approach is the use of the positive-definiteness requirement for the dual image of the absolute conic (DIAC). The problem is couched within a convex optimization framework and convergence to the global optimum is guaranteed. Experiments on various data sets indicate that the proposed algorithms more reliably deliver accurate and meaningful results. This work points the way to an alternative and more general approach to self-calibration using the advantageous properties of SDP. Algorithms are also discussed for cameras undergoing general motion.Keywords: Data sets; Dual image; General approach; Global optimum; Novel methods; Optimization framework; Self calibration; Self-calibrating; Semi-definite programming; Convex optimization; Medical imaging; Cameras200810.1109/DICTA.2008.462016-02-24