Real-time autonomous multi resolution visual surveys based on seafloor scene complexity
| Autor: | Kazunori Nagano, Yuya Nishida, Adrian Bodenmann, Toshihiro Maki, Blair Thornton, Yuto Otsuki |
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| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Measure (data warehouse) business.industry Computer science 02 engineering and technology 021001 nanoscience & nanotechnology Seafloor spreading Field (geography) 020901 industrial engineering & automation Multi resolution Feature (computer vision) Spatial ecology Robot Computer vision Artificial intelligence 0210 nano-technology business Image resolution Remote sensing |
| Zdroj: | 2016 IEEE/OES Autonomous Underwater Vehicles (AUV). |
| DOI: | 10.1109/auv.2016.7778692 |
| Popis: | This paper describes a method to optimize the spatial resolution of image surveys based on the spatial scale of features on the seafloor that are not known prior to observation. The method makes use of the density of visual features as a measure of the complexity of a seafloor image. In order to achieve this, two approaches to assess scene complexity we investigated. The performance of the method was verified using seafloor imagery obtained in the Iheya North field in the Okinawa Trough. The results demonstrate that it is effective for a large range of feature sizes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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