hlzhang525

3D Imaging (Point Cloud), Accuracy, and Serving

Blog Post created by hlzhang525 on Oct 21, 2014

Introduction

 

Airborne & terrestrial 3D mapping systems are widely available on the different platforms (airplane, helicopter, UAV, mobile-vehicle, etc.), which are mainly used to collect 3D imagery for civil mapping applications, including stereo-pair, point cloud, oblique, panoramas, motion video, and others. 


With 3D imaging technology, those ‘combined’ systems mostly produce very accurate 3D imagery (point cloud), while reaching very high-resolution geospatial details on the ground. One of the main reasons for high accuracy with the spatial details is:


Those mapping systems are commonly assembled with the Global Positioning System (GPS) and Inertial Navigation Systems (INS), in addition to high precision ‘civil-mapping’ sensors, scanners, or cameras.

 

GPS

The Global Positioning System can be used for determining one's precise location and providing a highly accurate time reference almost anywhere on Earth or in Earth orbit. The accuracy of the GPS signal itself is about 5 meters. However, using differential GPS and other error-correcting techniques, the accuracy can be improved to about 1 cm over short distances.

 

INS

An Inertial Navigation System provides the position, velocities and attitude of an aircraft by measuring the accelerations and rotations applied to the system's inertial frame. INS's have angular and linear accelerometers (for changes in position).

 

Angular accelerometers measure how the aircraft is rotating in space. Generally, there's at least one sensor for each of the three axes: pitch (nose up and down), yaw (nose left and right) and roll (clockwise or counterclockwise from the cockpit).

 

Linear accelerometers measure how the aircraft is moving in space. Since it can move in three axes (up & down, left & right, forward & back), there is a linear accelerometer for each axis. A computer continually calculates the aircraft's current position. First, for each of six axes, it integrates the sensed amount of acceleration over time to figure the current velocity. Then it integrates the velocity to figure the current position.


After acquisition (before serving, analysis, or extracting information),  3D imagery from those mapping systems must be processed by remote sensing specialists with proper ‘algorithm-enabled’ computer package for higher accuracy, in addition to other aspects (noise removal, color enhancement  ....)

 

Manage 3D Imaging and Point Clouds

 

Different data of 3D Imaging (and Point Clouds) will utilize different serving approach, when trying to manage at server-side, which will ensure that each can be effectively and seamlessly used in various applications.

 

In the market, some solution vendors offer specific server-side solution to manage certain type of 3D Imaging data directly at server-side, such as optical stereo-pair, optical oblique, optical panoramas, optical motion video, point cloud, or others.


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