Real-time dense 3D object reconstruction using RGB-D sensor

被引：0

作者：

Ruchay, Alexey ^{[1
,2
,3
]}

Dorofeev, Konstantin ^{[2
]}

Kalschikov, Vsevolod ^{[2
]}

机构：

[1] Russian Acad Sci, Fed Res Ctr Biol Syst & Agrotechnol, Orenburg, Russia

[2] Chelyabinsk State Univ, Dept Math, Chelyabinsk, Russia

[3] South Ural State Univ, Natl Res Univ, Dept Informat Secur, Chelyabinsk, Russia

来源：

APPLICATIONS OF DIGITAL IMAGE PROCESSING XLIII | 2020年 / 11510卷

关键词：

3D object reconstruction; RGB-D sensor; Iterative Closest Point;

D O I：

10.1117/12.2567253

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper, we propose a new algorithm for dense 3D object reconstruction using a RGB-D sensor at high rate. In order to obtain a dense shape recovery of a 3D object, an efficient merging of the current and incoming point clouds obtained with the Iterative Closest Point is suggested. As a result, incoming frames are aligned to the dense 3D model. The accuracy of the proposed 3D object reconstruction algorithm on real data is compared to that of the estate-of-the-art reconstruction algorithms.

引用

页数：7

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