Position Measurement Using Ultra-High Resolution 360-Degree Panoramic Images and Particle Swarm Optimization

碩士 === 國立臺北科技大學 === 土木與防災研究所 === 101 === The changing features of digital cameras in recent years enable the capturing of images in resolution as high as ten million pixels. Nevertheless, limited by camera angles and range, it is not always possible to capture what is in front of the eye in on...

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Bibliographic Details
Main Authors: Jian-An Wang, 王健安
Other Authors: Walter Chen
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/t39n22
Description
Summary:碩士 === 國立臺北科技大學 === 土木與防災研究所 === 101 === The changing features of digital cameras in recent years enable the capturing of images in resolution as high as ten million pixels. Nevertheless, limited by camera angles and range, it is not always possible to capture what is in front of the eye in one picture.Now, the GigaPan Robot Arm combined with any common digital camera makes image capturing in ultra-high resolution possible. In addition to its use in capturing and recording images, this study applied the combination of GigaPan and the PSO algorithm to locating spatial coordinates. Three capturing points were randomly selected around a target and their spatial coordinates were measured by GPS (and used as control points). At each of these points, one set of 360 degree high-resolution panoramic images were captured. Based on the theory that GigaPan can capture and record 360 degree panoramic images, it was possible to calculate the angle between any two objects and the capturing points with the pixels of the panoramic images. With this angle, virtual rays were simulated that streamed from the three capturing points to the target. With the rapid search feature of the PSO algorithm and based on the principle of triangulation, the three capturing points were examined randomly at 0~360 degrees. As different virtual rays moved towards minimum intersection areas among intersection unions, their intersections were the spatial coordinates of the target. Besides locating the spatial coordinates of a target, this study also applied the same method to: (1) locating the surroundings of a building, (2) observing the inclination angle of trees on a slope. The inclination angle was observed in images captured in different periods to see if it tended to increase, thus determining if the slope was in a stable state. Additionally, the angle was compared with the results from LiDAR scanning. The comparison shows that it is possible to obtain reasonable results using the combination of GigaPan and PSO, proving the application potential of this method.