Multi-Sensor Fusion Tracking Algorithm Based on Augmented Reality System

2020 ◽  
pp. 1-1
Author(s):  
Yujie Wang
2006 ◽  
Vol 15 (3) ◽  
pp. 336-340 ◽  
Author(s):  
Yue Liu ◽  
Yongtian Wang ◽  
Yu Li ◽  
Jinchao Lei ◽  
Liang Lin

Yuanmingyuan was called “Garden of All Gardens” before it was looted and burnt down by the Anglo-French allied forces in 1860. Nowadays there are only stone ruins that used to be parts of ancient buildings. The Digital Yuanmingyuan project is designed to provide visitors with the visualization of virtual reconstructions superimposed upon the natural field of the ruins using a personal AR (Augmented Reality) system. It can not only preserve the current appearance of the ruins, but also exhibit the original exquisite architecture of Yuanmingyuan. The technical difficulties of the system are analyzed, and the design of the system hardware and the tracking algorithm are discussed. A prototype of the proposed system is developed and the initial result of restoring one typical scene in Yuanmingyuan is presented.


Author(s):  
Shiqiang Hu ◽  
Zhongliang Jing

An approach of multi-sensor fusion tracking with extended Adalines model and fuzzy stochastic decision is proposed in this paper. The criterion of multi-sensor fuzzy stochastic decision is presented. An optimal algorithm for weight adjustment is designed combining genetic algorithm with fuzzy reasoning. This optimal algorithm has two important features: adaptation and learning; the effectiveness of the proposed method is illustrated through computer simulation under the circumstances of multi-sensor in target tracking.


10.5772/6161 ◽  
2008 ◽  
Author(s):  
Takafumi Sonoura ◽  
Takashi Yoshimi ◽  
Manabu Nishiyama ◽  
Hideichi Nakamoto ◽  
Seiji Tokura ◽  
...  

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1325 ◽  
Author(s):  
Kumar ◽  
Patil ◽  
Kang ◽  
Chai

Augmented reality (AR) systems are becoming next-generation technologies to intelligently visualize the real world in 3D. This research proposes a sensor fusion based pipeline inspection and retrofitting for the AR system, which can be used in pipeline inspection and retrofitting processes in industrial plants. The proposed methodology utilizes a prebuilt 3D point cloud data of the environment, real-time Light Detection and Ranging (LiDAR) scan and image sequence from the camera. First, we estimate the current pose of the sensors platform by matching the LiDAR scan and the prebuilt point cloud data from the current pose prebuilt point cloud data augmented on to the camera image by utilizing the LiDAR and camera calibration parameters. Next, based on the user selection in the augmented view, geometric parameters of a pipe are estimated. In addition to pipe parameter estimation, retrofitting in the existing plant using augmented scene are illustrated. Finally, step-by-step procedure of the proposed method was experimentally verified at a water treatment plant. Result shows that the integration of AR with building information modelling (BIM) greatly benefits the post-occupancy evaluation process or pre-retrofitting and renovation process for identifying, evaluating, and updating the geometric specifications of a construction environment.


Author(s):  
Peng Wang ◽  
Huitong Fu ◽  
Xiaoyan Li ◽  
Jia Guo ◽  
Zhigang Lv ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document