{"title":"彩色图像序列中目标关联与跟踪的两种相似度统计方法","authors":"H. L. Kennedy","doi":"10.1109/ICIP.2007.4379196","DOIUrl":null,"url":null,"abstract":"Two statistical measures of similarity, for data association and tracking moving objects in sequences of color images, are derived and their performance is compared with normalized cross-correlation. Both methods use an F-distributed test statistic in a hypothesis test, which permits association thresholds to be set to give the desired (theoretical) false-association rate. One of the methods matches the performance of normalized cross-correlation, in the test data used, and is computationally less expensive.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Two Statistical Measures of Similarity for Object Association and Tracking in Color Image Sequences\",\"authors\":\"H. L. Kennedy\",\"doi\":\"10.1109/ICIP.2007.4379196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two statistical measures of similarity, for data association and tracking moving objects in sequences of color images, are derived and their performance is compared with normalized cross-correlation. Both methods use an F-distributed test statistic in a hypothesis test, which permits association thresholds to be set to give the desired (theoretical) false-association rate. One of the methods matches the performance of normalized cross-correlation, in the test data used, and is computationally less expensive.\",\"PeriodicalId\":131177,\"journal\":{\"name\":\"2007 IEEE International Conference on Image Processing\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Conference on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2007.4379196\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2007.4379196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Two Statistical Measures of Similarity for Object Association and Tracking in Color Image Sequences
Two statistical measures of similarity, for data association and tracking moving objects in sequences of color images, are derived and their performance is compared with normalized cross-correlation. Both methods use an F-distributed test statistic in a hypothesis test, which permits association thresholds to be set to give the desired (theoretical) false-association rate. One of the methods matches the performance of normalized cross-correlation, in the test data used, and is computationally less expensive.