{"title":"表示和识别监控应用中的复杂事件","authors":"L. Snidaro, Massimo Belluz, G. Foresti","doi":"10.1109/AVSS.2007.4425360","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the problem of representing and maintaining rule knowledge for a video surveillance application. We focus on complex events representation which cannot be straightforwardly represented by canonical means. In particular, we highlight the ongoing efforts for a unifying framework for computable rule and taxonomical knowledge representation.","PeriodicalId":371050,"journal":{"name":"2007 IEEE Conference on Advanced Video and Signal Based Surveillance","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Representing and recognizing complex events in surveillance applications\",\"authors\":\"L. Snidaro, Massimo Belluz, G. Foresti\",\"doi\":\"10.1109/AVSS.2007.4425360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate the problem of representing and maintaining rule knowledge for a video surveillance application. We focus on complex events representation which cannot be straightforwardly represented by canonical means. In particular, we highlight the ongoing efforts for a unifying framework for computable rule and taxonomical knowledge representation.\",\"PeriodicalId\":371050,\"journal\":{\"name\":\"2007 IEEE Conference on Advanced Video and Signal Based Surveillance\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Conference on Advanced Video and Signal Based Surveillance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AVSS.2007.4425360\",\"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 Conference on Advanced Video and Signal Based Surveillance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AVSS.2007.4425360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Representing and recognizing complex events in surveillance applications
In this paper, we investigate the problem of representing and maintaining rule knowledge for a video surveillance application. We focus on complex events representation which cannot be straightforwardly represented by canonical means. In particular, we highlight the ongoing efforts for a unifying framework for computable rule and taxonomical knowledge representation.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
