{"title":"基于形状空间的鱼类识别","authors":"K. Nasreddine, A. Benzinou","doi":"10.1109/EUSIPCO.2015.7362362","DOIUrl":null,"url":null,"abstract":"Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we introduce a preliminary step of pose estimation for accelerating the processing time. We then show that shape geodesics may also be used for outline-based fish recognition. Experiments conducted on the SQUID database which is used as a benchmark to evaluate fish shape recognition, show (1) a reduction in computation time of a factor of ten in average, and (2) the outperformance of the proposed scheme compared to previous methods.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Shape-based fish recognition via shape space\",\"authors\":\"K. Nasreddine, A. Benzinou\",\"doi\":\"10.1109/EUSIPCO.2015.7362362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we introduce a preliminary step of pose estimation for accelerating the processing time. We then show that shape geodesics may also be used for outline-based fish recognition. Experiments conducted on the SQUID database which is used as a benchmark to evaluate fish shape recognition, show (1) a reduction in computation time of a factor of ten in average, and (2) the outperformance of the proposed scheme compared to previous methods.\",\"PeriodicalId\":401040,\"journal\":{\"name\":\"2015 23rd European Signal Processing Conference (EUSIPCO)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 23rd European Signal Processing Conference (EUSIPCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EUSIPCO.2015.7362362\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 23rd European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUSIPCO.2015.7362362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we introduce a preliminary step of pose estimation for accelerating the processing time. We then show that shape geodesics may also be used for outline-based fish recognition. Experiments conducted on the SQUID database which is used as a benchmark to evaluate fish shape recognition, show (1) a reduction in computation time of a factor of ten in average, and (2) the outperformance of the proposed scheme compared to previous methods.