3D Reconstruction of Indoor Scenes Using RGB-D Monocular Vision

2016 ◽  
Author(s):  
Sanmao Liu ◽  
Wenqiu Zhu ◽  
Canqing Zhang ◽  
Wenjing Sun
Keyword(s):  
3D Reconstruction ◽  
Monocular Vision ◽  
Indoor Scenes

scholarly journals A Real-Time Online Learning Framework for Joint 3D Reconstruction and Semantic Segmentation of Indoor Scenes

2021 ◽  
pp. 1-1
Author(s):  
Davide Menini ◽  
Suryansh Kumar ◽  
Martin R. Oswald ◽  
Erik Sandstrom ◽  
Cristian Sminchisescu ◽  
...  
Keyword(s):  
Online Learning ◽  
3D Reconstruction ◽  
Real Time ◽  
Semantic Segmentation ◽  
Learning Framework ◽  
Indoor Scenes

A semi-interactive panorama based 3D reconstruction framework for indoor scenes

2011 ◽  
Vol 115 (11) ◽  
pp. 1516-1524 ◽  
Author(s):  
Trung Kien Dang ◽  
Marcel Worring ◽  
The Duy Bui
Keyword(s):  
3D Reconstruction ◽  
Indoor Scenes

scholarly journals A Post-Rectification Approach of Depth Images of Kinect v2 for 3D Reconstruction of Indoor Scenes

2017 ◽  
Vol 6 (11) ◽  
pp. 349 ◽  
Author(s):  
Jichao Jiao ◽  
Libin Yuan ◽  
Weihua Tang ◽  
Zhongliang Deng ◽  
Qi Wu
Keyword(s):  
3D Reconstruction ◽  
Kinect V2 ◽  
Depth Images ◽  
Indoor Scenes

scholarly journals A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Panlong Gu ◽  
Fengyu Zhou ◽  
Dianguo Yu ◽  
Fang Wan ◽  
Wei Wang ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
Large Scale ◽  
Reconstruction Method ◽  
Loop Closure ◽  
Mapping Algorithm ◽  
Localization And Mapping ◽  
Indoor Scenes ◽  
Slam Algorithm ◽  
Robot Position

RGBD camera-based VSLAM (Visual Simultaneous Localization and Mapping) algorithm is usually applied to assist robots with real-time mapping. However, due to the limited measuring principle, accuracy, and distance of the equipped camera, this algorithm has typical disadvantages in the large and dynamic scenes with complex lightings, such as poor mapping accuracy, easy loss of robot position, and much cost on computing resources. Regarding these issues, this paper proposes a new method of 3D interior construction, which combines laser radar and an RGBD camera. Meanwhile, it is developed based on the Cartographer laser SLAM algorithm. The proposed method mainly takes two steps. The first step is to do the 3D reconstruction using the Cartographer algorithm and RGBD camera. It firstly applies the Cartographer algorithm to calculate the pose of the RGBD camera and to generate a submap. Then, a real-time 3D point cloud generated by using the RGBD camera is inserted into the submap, and the real-time interior construction is finished. The second step is to improve Cartographer loop-closure quality by the visual loop-closure for the sake of correcting the generated map. Compared with traditional methods in large-scale indoor scenes, the proposed algorithm in this paper shows higher precision, faster speed, and stronger robustness in such contexts, especially with complex light and dynamic objects, respectively.

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