19 September 2017 Accurate generation of the 3D map of environment with a RGB-D camera
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With the development of RGB-D sensors, a new alternative to generation of 3D maps is appeared. First, features extracted from color and depth images are used to localize them in a 3D scene. Next, Iterative Closest Point (ICP) algorithm is used to align RGB-D frames. As a result, a new frame is added to the dense 3D model. However, the spatial distribution and resolution of depth data affect to the performance of 3D scene reconstruction systems based on ICP. In this paper we propose to divide the depth data into sub-clouds with similar resolution, to align them separately, and unify in the entire points cloud. The presented computer simulation results show an improvement in accuracy of 3D scene reconstruction using real indoor environment data.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jose A. González-Fraga, Jose A. González-Fraga, Vitaly Kober, Vitaly Kober, Victor H. Diaz-Ramirez, Victor H. Diaz-Ramirez, Everardo Gutierrez, Everardo Gutierrez, Omar Alvarez-Xochihua, Omar Alvarez-Xochihua, "Accurate generation of the 3D map of environment with a RGB-D camera", Proc. SPIE 10396, Applications of Digital Image Processing XL, 103962A (19 September 2017); doi: 10.1117/12.2273074; https://doi.org/10.1117/12.2273074


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