Citation Context

...process is the non-linear minimization of the reprojection error, or bundle adjustment (BA). The best performing BA software available publicly is Sparse Bundle Adjustment (SBA) by Lourakis & Argyros =-=[9]-=-. The key to its high performance is the use of the so called Schur complement trick [19] to reduce the size of the linear system (also known as the normal equations) that needs to be solved in each i...

Citation Context

...viously collected frames. We show that globally consistent alignments can be achieved either via highly efficient pose graph optimization such as TORO [17, 31, 24, 54] or via sparse bundle adjustment =-=[29, 26]-=-.RGB-D Mapping 3 The overall system can accurately align and map large indoor environments in nearreal time and is capable of handling situations such as featureless corridors and completely dark roo...

Citation Context

...me as a 3-vector ri representing the imaginary parts of qi. Thus, the ith camera pose is fully specified by: xi = (r ⊤ i ,t ⊤ i ) ⊤ . (4) For BA, we employ the well known high-performance SBA library =-=[16]-=-. The sparse Jacobian J used for the LevenbergMarquardt algorithm is: J = ∂ˆz(p) ∂p . (5) The accuracy of a specific SLAM setting is evaluated using backward propagation of covariance [11, pp. 141]. T...

Citation Context

...ve ICP step was not necessary. Therefore, they improved the algorithm so that ICP was only used if few (or none) keypoint matches could be established. While Henry et al. use sparse bundle adjustment =-=[19]-=- for the optimization of the 2.5D reprojection errors in RGB-D image space, we optimize the 3D pose graph using the g2o [18] framework. Finally, the post-processing of the two approaches is different:...

Citation Context

...much smaller than the number of points, the Schur complement method can reduce the factorization time by a large constant factor. One impressive example of this algorithm is Lourakis and Argyros’ SBA =-=[9]-=- used by Photo Tourism [14]. For conjugate gradient methods, the dominant computation is the matrix-vector multiplications in multiple CG iteration, of which the time complexity is determined by the s...

Citation Context

...justment algorithms has become a critical issue. The basic mathematics of the bundle adjustment problem are well understood [4], and there is also a freely available high-quality implementation – SBA =-=[5]-=-. SBA is based on a dense Cholesky factorization of the reduced camera matrix. It has space complexity that is quadratic and time complexity that is cubic in the number of photos. While this works wel...

Citation Context

...re, as there are 3n unknowns, the linear system is solved by finding the four eigenvectors with lowest eigenvalue of a 3n ⇥ 3n matrix. Bundle adjustment and dense 3D recovery: We used the SBA code by =-=[23]-=- for the smaller sets and PBA [24] for the larger sets. We apply dense reconstruction of the scene, e.g., using [25]. VI. EXPERIMENTS We tested our method on several real image sequences. We first sho...

Citation Context

...r of implementation details, by using an inlier limit and the truncated quadratic cost function. Finally, the accuracy of the proposed LO + method is tested within a standard Bundle adjustment method =-=[12]-=-. Perhaps surprisingly the bundler is rather sensitive to initialization. The LO initialized non-linear optimization is always superior in terms of residual errors to the Gold Standard method advocate...

Citation Context

...orithms become brittle, e.g. Liu et al. [18] demonstrate several cases where the Voodoo tracker1 fails, and similarly Hedborg et al. [12] demonstrate failure of the SBA package of Lourakis and Agyros =-=[19]-=- under rolling shutter. 1.1. Related work Bundle adjustment (BA) is a collective name for techniques that refine an initial estimate of structure and camera motion, by minimising the reprojection erro...