@inproceedings{0ea50131ab6b4d17ae4b3a82f772c70e,
title = "Accurate generation of the 3D map of environment with a RGB-D camera",
abstract = "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.",
keywords = "3D mapping, feature detector, matching, registration",
author = "Gonz{\'a}lez-Fraga, {Jose A.} and Vitaly Kober and Diaz-Ramirez, {Victor H.} and Everardo Gutierrez and Omar Alvarez-Xochihua",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; Applications of Digital Image Processing XL 2017 ; Conference date: 07-08-2017 Through 10-08-2017",
year = "2017",
doi = "10.1117/12.2273074",
language = "Ingl{\'e}s",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Tescher, {Andrew G.}",
booktitle = "Applications of Digital Image Processing XL",
address = "Estados Unidos",
}