Author:
Shahid Ismail Ghalif,Phang Swee King,Chew Wei Jen
Abstract
Abstract
The photogrammetric method of 3D mapping uses Structure from Motion (SfM) algorithm, where 3D structures of a scene are created from 2D sets of data taken from multiple angles. This 3D mapping process is used in many advanced and important applications in the digital and robotics industry. The use of omnidirectional camera along with UAV for this photogrammetric process allows faster data acquisition and data processing to construct 3D structures compared to traditional method. However, the metric accuracy of spherical photogrammetry is relatively less compared to traditional framed camera photogrammetry. Hence, this research will focus on improving metric accuracy of spherical photogrammetry by enhancing SfM algorithm for the purpose of providing an enhanced and value-added fast 3D mapping solution using UAV. The research was conducted at 4 main levels. 1) Data acquisition phase, where the 360-degree camera with GPS tracker are attached to a UAV, and it is used to collect different sets of images at different heights and angles. 2) Camera calibration, for the purpose of identifying the camera intrinsic and extrinsic. These 2 parameters are crucial in feature detection and camera position estimation. 3) Data processing phase, where the collected data would be processed through the enhanced SfM algorithm to create the 3D structures. 4) Data analysis phase, where the 3D model created from enhanced SfM algorithm would be compared against a reference 3D model created by commercial software. However, the results attained were not as expected due to undesired feature detection process. This research is expected to help geographical and land surveyors to conduct surveys at a faster, more efficient and at a higher accuracy. A practical use case of this solution is to survey the terrain of an area under natural disaster, accurately and faster for search and rescue missions.
Subject
Computer Science Applications,History,Education
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