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Coarse rigid transformations determined in this step enable fine alignment with dense, unfiltered point clouds or using Iterative Common Point (ICP) alignment techniques.
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The fine alignment stage with the 10-state Kalman filter refines the initial estimate of the transformation matrix given by the coarse alignment algorithm.
The IMOD package was used for rough alignment with the fine alignment and reconstruction performed using the TxBR package.
The IMOD package was used for a rough alignment with the fine alignment and reconstruction performed using the TxBR package.
The IMOD package (http://bio3d.colorado.edu/imod/) was used for rough alignment with the fine alignment and reconstruction was performed using the TxBR package (National Center for Microscopy and Imaging Research, San Diego, CA, USA).
After having successfully applied the described multi-view coarse registration technique to a given dataset, we have the possibility to complete the alignment process toward a high-precision object modeling with a fine alignment and/or global adjustment step.
Several moving conditions of carrier are assumed to test the new alignment method, and the results indicate that the initial attitude angles can be achieved with small errors, which is suitable for the conventional fine alignment afterward.
This demonstrates that the coarse alignment obtained with our approach is good enough to bring the multi-view fine alignment stage to converge to the correct solution.
Coarse alignment and fine alignment could work together to achieve the perfect alignment.
Generally, the initial alignment is divided into coarse and fine alignment.
For example, large windows for coarse alignment followed by smaller windows for fine alignment are very useful.
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