A High Resolution Optical Satellite Image Dataset for Ship Recognition and Some New Baselines
Liu ZK(刘子坤)1,2; Yuan L(袁柳)3; Weng LB(翁璐斌)1; Yang YP(杨一平)1; Weng LB(翁璐斌)
2017-03
会议日期February 24-26, 2017
会议地点Porto - Portugal
关键词High Resolution Optical Remote Sensing Image Sea-land Segmentation Ship Detection Ship Recognition Dataset
DOI10.5220/0006120603240331
英文摘要Ship recognition in high-resolution optical satellite images is an important task. However, it is difficult to recognize ships under complex backgrounds, which is the main bottleneck for ship recognition and needs to be further explored and researched. As far as we know, there is no public remote sensing ship dataset and few open source work. To facilitate future ship recognition related research, in this paper, we present a public high-resolution ship dataset, “HRSC2016”, that covers not only bounding-box labeling way, but also rotated bounding box way with three-level classes including ship, ship category and ship types. We also provide the ship head position for all the ships with “V” shape heads and the segmentation mask for every image in “Test set”. Besides, we volunteer a ship annotation tool and some development tools. Given these rich annotations we perform a detailed analysis of some state-of-the-art methods, introduce a novel metric, the separation fitness (SF), that is used for evaluating the performance of the sea-land segmentation task and we also build some new baselines for recognition. The latest dataset can be downloaded from “http://www.escience.cn/people/liuzikun/DataSet.html”.
内容类型会议论文
源URL[http://ir.ia.ac.cn/handle/173211/14545]  
专题自动化研究所_综合信息系统研究中心
通讯作者Weng LB(翁璐斌)
作者单位1.Institute of Automation Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190, Beijing, China
2.University of Chinese Academy of Sciences, 80 Zhongguancun East Road, 100190, Beijing, China
3.China Academy of Electronics and Information Technology, 11 Shuanyuan Road, 100041, Beijing, China
推荐引用方式
GB/T 7714
Liu ZK,Yuan L,Weng LB,et al. A High Resolution Optical Satellite Image Dataset for Ship Recognition and Some New Baselines[C]. 见:. Porto - Portugal. February 24-26, 2017.
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