While electric observer systems (EOS) have been popularly installed in fishing vessels to record fish catch videos and geographic information, such systems still require human interventions to manually extract fish catch data from raw videos. Therefore, we propose an automatic video processing pipeline in this research to detect fish catches in real time from videos. For optimizing the system. This research tries to find out how to get fish data including catch time, Latitude, Longitude, category and fish length automatized. Then transport this data to server by satellite transmission to reduce error by human. We expect that the intelligence system can work effective in the future. In this research, the intelligent EOS can apply on simulation environment efficiently because of its higher camera resolution, reducing impact of fish men and fishing gear. However, this system can only get about 75% of correct rate in real environment.
|Number of pages||9|
|Journal||Journal of Taiwan Society of Naval Architects and Marine Engineers|
|Publication status||Published - 2018 Jan 1|
All Science Journal Classification (ASJC) codes
- Ocean Engineering
- Mechanical Engineering