Invention Grant
- Patent Title: Automatic ship tracking method and system based on deep learning network and mean shift
-
Application No.: US16627485Application Date: 2018-12-11
-
Publication No.: US10706285B2Publication Date: 2020-07-07
- Inventor: Lianbing Deng
- Applicant: ZHUHAI DA HENGQIN TECHNOLOGY DEVELOPMENT CO., LTD.
- Applicant Address: CN Zhuhai
- Assignee: ZHUHAI DA HENGQIN TECHNOLOGY DEVELOPMENT CO., LTD.
- Current Assignee: ZHUHAI DA HENGQIN TECHNOLOGY DEVELOPMENT CO., LTD.
- Current Assignee Address: CN Zhuhai
- Agency: Bayramoglu Law Office LLC
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@53f2363d
- International Application: PCT/CN2018/120294 WO 20181211
- International Announcement: WO2019/101220 WO 20190531
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N3/08 ; G06T7/277 ; G06T7/11 ; G06K9/62

Abstract:
An automatic ship tracking method and system based on deep learning network and mean shift, wherein the method includes: collecting surveillance video data which includes collecting coastal region surveillance video data under visible light and extracting each frame of image; performing preprocessing to extract a positive sample and a negative sample of a ship target; inputting the samples of the ship target in the video into a neural network to train a model by a region-based convolutional neural network method; extracting initial frame data of the video and performing ship detection and probability density calculation on initial moment data according to the trained model; and determining a ship tracking result at the current moment by a calculation result of a previous moment.
Public/Granted literature
- US20200160061A1 AUTOMATIC SHIP TRACKING METHOD AND SYSTEM BASED ON DEEP LEARNING NETWORK AND MEAN SHIFT Public/Granted day:2020-05-21
Information query