Abstract No.F180130-142
Author name(s): Heesu Kim1, Evangelos Boulougouris1, Sanghyun Kim2
Company: 1. University of Strathclyde, UK; 2. Inha University, Korea
The purpose of this research is development of vision-based object detection algorithm that recognizes a marine object, localizes the object on captured frames, and estimates the distance to the object. Faster R-CNN and stereo vision based depth estimation are combined for real-time marine object detection. The performance of this algorithm is verified by model ship detection test in towing tank. The test results showed that this algorithm is potentially applicable to real USV.
KEY WORDS: unmanned surface vehicle; vision-based object detection; faster region with convolutional neural network; depth estimation
All Rights Reserved. If you need the entire text, please contact the author or intl.exchange@ssnaoe.org