Motion Estimation byUsing Stereo Vision Analysis For Underwater Observation System
| Autor: | Masyhuri Husna Binti Mazlan, Morisawa Daisuke, Shimizu Junji, Koike Yoshikazu, Shimizu Etsuro, Enomoto Eriko, Sakata Kunio, Hirohashi Noritaka |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Iterative closest point Triangulation (computer vision) Motion detection Stereopsis Feature (computer vision) Motion estimation Computer vision Artificial intelligence Underwater business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | ICEIC |
| Popis: | In this paper, motion estimation by using stereo vision analysis for underwater observation system (UOS) is presented. We developed a free-fall type UOS which was built with a glass sphere named Gyogyotto Camera. The UOS is employed to observe the underwater environment using the camera built inside of the glass sphere. The recorded images are used for stereo vision analysis to detect the motion estimation of the UOS. The proposed motion estimation uses Speed Up Robust Feature (SURF), stereo triangulation and Iterative Closest Point (ICP) algorithm. At first, calibration result with or without glass sphere on the land is described. The calibration result for underwater is also presented. Comparing the obtained results, we discussed the influence of the glass sphere. Moreover, we tried to estimate the motion of the camera by using the proposed method on the land and discuss the effective extraction of the feature points for underwater environment. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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