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This paper presents a solution to the Projective Structure from Motion (PSfM) problem able to deal efficiently with missing data, outliers and, for the first time, large scale 3D reconstruction scenarios. By embedding the projective depths into the projective parameters of the points and views, we decrease the number of unknowns to estimate and improve computational speed by optimizing standard linear...
Allowing for a priori optimization of the robot manipulation to improve the performance in the unmanned environment, it is critical for the augmented reality system to estimate the attitude of point clouds in model reconstruction. The estimation of planar parameter is not always faithful for point cloud fitting, because the gross errors and outliers are not considered in by the traditional plane fitting...
This paper presents approximate methods to estimate iso-values in 3D thermal model reconstruction of indoor environments. The input data is represented in the form of registered point clouds with added temperature information obtained using 3D laser scanner and thermal imaging camera. They are then registered to the common coordinate system using SLAM6D. Marching cubes based algorithm for point cloud...
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