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题名:
Mine like object detection and recognition based on intrackability and improved BOW
作者: Yu SQ(余思泉); Shao, Jinxin; Han Z(韩志); Gao L(高雷); Lin Y(林扬); Tang YD(唐延东); Wu CD(吴成东)
作者部门: 机器人学研究室
通讯作者: 韩志
会议名称: 6th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2016
会议日期: June 19-22, 2016
会议地点: Chengdu, China
会议录: 6th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2016
会议录出版者: IEEE
会议录出版地: Piscataway, NJ, USA
出版日期: 2016
页码: 222-227
收录类别: EI ; CPCI(ISTP)
ISSN号: 2379-7711
ISBN号: 978-1-5090-2732-3
摘要: In this paper, we present an automatic system of mine like object detection and recognition for sonar videos. This system is implemented with two main methods. One is the object detection and segmentation with intrackability, another is object recognition of mine like based on improved BOW algorithm and Support Vector Machine (SVM). Intrackability is defined by the concept of entropy, and can reflect the difficulty and uncertainty in tracking certain elements on the time axis. Therefore, our segmentation and detection method can effectively eliminate complex noise in sonar image to guarantee the more accurate object segmentation and detection. In our recognition method of mine like object, we use an improved BOW and SVM to implement the more accurate recognition for mine like objects. In the method, an improved BOW algorithm is utilized for image feature extraction, due to that it can represent local and global feature of image in a more comprehensive way; and then the object recognition is implemented with SVM. Our extensive experiments show that our system can accurately detect and recognize mine like objects in real-time.
语种: 英语
产权排序: 1
EI收录号: 20164302940167
WOS记录号: WOS:000389835200042
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/19304
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
Yu SQ,Shao, Jinxin,Han Z,et al. Mine like object detection and recognition based on intrackability and improved BOW[C]. 6th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2016. Chengdu, China. June 19-22, 2016.Mine like object detection and recognition based on intrackability and improved BOW.
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文件名: Mine like object detection and recognition based on intrackability and improved BOW.pdf
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