Real-time point-cloud data transmission for teleoperation using H.264/AVC

2014 ◽  
Author(s):  
Ga-Ram Jang ◽  
Yong-Deuk Shin ◽  
Jae-Han Park ◽  
Moon-Hong Baeg
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Time Point

scholarly journals A Mobile Augmented Reality System for the Real-Time Visualization of Pipes in Point Cloud Data with a Depth Sensor

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 836 ◽  
Author(s):  
Young-Hoon Jin ◽  
In-Tae Hwang ◽  
Won-Hyung Lee
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Point Cloud ◽  
Depth Image ◽  
Visualization Method ◽  
Point Cloud Data ◽  
Matching Method ◽  
The Real ◽  
Cloud Data ◽  
Real Time Visualization

Augmented reality (AR) is a useful visualization technology that displays information by adding virtual images to the real world. In AR systems that require three-dimensional information, point cloud data is easy to use after real-time acquisition, however, it is difficult to measure and visualize real-time objects due to the large amount of data and a matching process. In this paper we explored a method of estimating pipes from point cloud data and visualizing them in real-time through augmented reality devices. In general, pipe estimation in a point cloud uses a Hough transform and is performed through a preprocessing process, such as noise filtering, normal estimation, or segmentation. However, there is a disadvantage in that the execution time is slow due to a large amount of computation. Therefore, for the real-time visualization in augmented reality devices, the fast cylinder matching method using random sample consensus (RANSAC) is required. In this paper, we proposed parallel processing, multiple frames, adjustable scale, and error correction for real-time visualization. The real-time visualization method through the augmented reality device obtained a depth image from the sensor and configured a uniform point cloud using a voxel grid algorithm. The constructed data was analyzed according to the fast cylinder matching method using RANSAC. The real-time visualization method through augmented reality devices is expected to be used to identify problems, such as the sagging of pipes, through real-time measurements at plant sites due to the spread of various AR devices.

scholarly journals Real-time Polygon Generation and Texture Mapping for Tele-operation using 3D Point Cloud Data

2013 ◽  
Vol 19 (10) ◽  
pp. 928-935 ◽  
Author(s):  
Ga-Ram Jang ◽  
Yong-Deuk Shin ◽  
Jae-Shik Yoon ◽  
Jae-Han Park ◽  
Ji-Hun Bae ◽  
...  
Keyword(s):  
Real Time ◽  
Point Cloud ◽  
Texture Mapping ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data

scholarly journals Intelligent warehouse monitoring based on distributed system and edge computing

2021 ◽  
Author(s):  
Sen Lin ◽  
Jianxin Huang ◽  
Wenzhou Chen ◽  
Wenlong Zhou ◽  
Jinhong Xu ◽  
...  
Keyword(s):  
Distributed System ◽  
Data Transmission ◽  
Point Cloud ◽  
Edge Computing ◽  
Point Cloud Data ◽  
Volume Calculation ◽  
Cloud Data ◽  
Material Volume ◽  
Sand And Gravel ◽  
Centralized System

AbstractThis paper mainly focuses on the volume calculation of materials in the warehouse where sand and gravel materials are stored and monitored whether materials are lacking in real-time. Specifically, we proposed the sandpile model and the point cloud projection obtained from the LiDAR sensors to calculate the material volume. We use distributed edge computing modules to build a centralized system and transmit data remotely through a high-power wireless network, which solves sensor placement and data transmission in a complex warehouse environment. Our centralized system can also reduce worker participation in a harsh factorial environment. Furthermore, the point cloud data of the warehouse is colored to visualize the actual factorial environment. Our centralized system has been deployed in the real factorial environment and got a good performance.

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