{"title":"一种视频机场目标识别方法","authors":"Yongmei Zhang, Chao Feng, Kuo Xing, Jiong Peng","doi":"10.1145/3268866.3268869","DOIUrl":null,"url":null,"abstract":"Aiming at the problem of lower recognition accuracy of video airport targets under complex conditions, the paper proposes a video airport target recognition method. The paper uses clustering method to extract the key-frames containing airport targets. According to the morphological processing results and the extracted contour features, the paper recognizes multiple potential areas including airport targets, and adopts Adaboost method based on Support Vector Machine (SVM) to recognize airport targets. The experimental results show the method can accurately recognize video airport targets.","PeriodicalId":285628,"journal":{"name":"Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition","volume":"147 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Video Airport Target Recognition Method\",\"authors\":\"Yongmei Zhang, Chao Feng, Kuo Xing, Jiong Peng\",\"doi\":\"10.1145/3268866.3268869\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem of lower recognition accuracy of video airport targets under complex conditions, the paper proposes a video airport target recognition method. The paper uses clustering method to extract the key-frames containing airport targets. According to the morphological processing results and the extracted contour features, the paper recognizes multiple potential areas including airport targets, and adopts Adaboost method based on Support Vector Machine (SVM) to recognize airport targets. The experimental results show the method can accurately recognize video airport targets.\",\"PeriodicalId\":285628,\"journal\":{\"name\":\"Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition\",\"volume\":\"147 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3268866.3268869\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3268866.3268869","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Aiming at the problem of lower recognition accuracy of video airport targets under complex conditions, the paper proposes a video airport target recognition method. The paper uses clustering method to extract the key-frames containing airport targets. According to the morphological processing results and the extracted contour features, the paper recognizes multiple potential areas including airport targets, and adopts Adaboost method based on Support Vector Machine (SVM) to recognize airport targets. The experimental results show the method can accurately recognize video airport targets.