{"title":"运动图像元数据标准有助于对象和活动分类","authors":"Darrell L. Young","doi":"10.1109/AIPR.2010.5759700","DOIUrl":null,"url":null,"abstract":"Metadata is considered vital in making sense of ISR sensor data because it provides the context needed to interpret motion imagery. For example, metadata provides the fundamental information needed to associate the imagery with location and time. But, more than that, metadata provides information that can assist in automated video analysis. This paper describes some of the ways that metadata can be used to improve automated video processing.","PeriodicalId":128378,"journal":{"name":"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Motion imagery metadata standards assist in object and activity classification\",\"authors\":\"Darrell L. Young\",\"doi\":\"10.1109/AIPR.2010.5759700\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Metadata is considered vital in making sense of ISR sensor data because it provides the context needed to interpret motion imagery. For example, metadata provides the fundamental information needed to associate the imagery with location and time. But, more than that, metadata provides information that can assist in automated video analysis. This paper describes some of the ways that metadata can be used to improve automated video processing.\",\"PeriodicalId\":128378,\"journal\":{\"name\":\"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2010.5759700\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2010.5759700","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Motion imagery metadata standards assist in object and activity classification
Metadata is considered vital in making sense of ISR sensor data because it provides the context needed to interpret motion imagery. For example, metadata provides the fundamental information needed to associate the imagery with location and time. But, more than that, metadata provides information that can assist in automated video analysis. This paper describes some of the ways that metadata can be used to improve automated video processing.