Bundle Adjustment Method using Sparse BFGS Solution

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文件名称：Bundle Adjustment Method using Sparse BFGS Solution
文件大小：1.11MB
文件格式：PDF
更新时间：2022-03-30 07:31:30
BA This letter introduces an efficient bundle adjustment (BA) method based on the sparse Broyden-Fletcher-Goldfarb-Shanno (sparse BFGS, sBFGS) solution, which efficiently estimates camera poses and 3-D points. The Levenberg-Marquardt (LM) solution, which is widely applied in BA problems, requires more linear equation solution and more iterations. A gain matrix calculated using both the Jacobian matrix and residual vector replaces the simple diagonal matrix of the LM solution, which results in a better estimation of the descent direction and step size when finding a path to a local minimum in a sparse BFGS solution. Four datasets were verified, and the results demonstrate that the proposed method requires fewer linear equation solutions to converge to a minimum compared with that of the LM-based BA method.