Geographical Location Estimation based on An Improved Particle Swarm Optimization
- Zhuojie Chen
- Lang Deng
- Yuanbiao Zhang
Abstract
This study presents a strategy for determining the relatively accurate geographical location of an object based on a video or a sequence of images taken at regular intervals. On the basis of a series of solar formulas, a precise object’s shadow length model that includes the latitude and longitude of the photographer is built to describe how the shadow changes. Inputting the shadow length of the object and the creation time of the image into the built model, parameters like the latitude or longitude can be estimated by Particle Swarm Optimization (PSO). To solve the problem that PSO is easy to get stuck into local optima, a compression factor and mutation operation are introduced to the algorithm. Through analyzing the instance, the improved PSO algorithm has demonstrated itself with enhancement in convergence and accuracy. In conclusion, the improved PSO is an effective and precise tool to estimate the geographical location of video or images.- Full Text: PDF
- DOI:10.5539/apr.v8n4p20
This work is licensed under a Creative Commons Attribution 4.0 License.
Journal Metrics
Google-based Impact Factor (2017): 3.90
h-index (November 2017): 17
i10-index (November 2017): 33
h5-index (November 2017): 12
h5-median (November 2017): 19
Index
- Bibliography and Index of Geology
- Civil Engineering Abstracts
- CNKI Scholar
- CrossRef
- EBSCOhost
- Excellence in Research for Australia (ERA)
- Google Scholar
- Infotrieve
- LOCKSS
- NewJour
- Open J-Gate
- PKP Open Archives Harvester
- SHERPA/RoMEO
- Standard Periodical Directory
- Ulrich's
- Universe Digital Library
- WorldCat
Contact
- William ChenEditorial Assistant
- apr@ccsenet.org