{"title":"基于时间的hmm视觉入侵检测","authors":"Vera M. Kettnaker","doi":"10.1109/CVPRW.2003.10035","DOIUrl":null,"url":null,"abstract":"We propose a new Hidden Markov Model with time-dependent states. Estimation of this model is shown to be as fast and easy as the estimation of regular HMMs. We demonstrate the usefulness and feasibility of such time-dependent HMMs with an application in which illegitimate access to personnel-only rooms in airports etc. can be distinguished from access by legitimate personnel, based on differences in the time of access or differences in the motion trajectories.","PeriodicalId":121249,"journal":{"name":"2003 Conference on Computer Vision and Pattern Recognition Workshop","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Time-dependent HMMs for visual intrusion detection\",\"authors\":\"Vera M. Kettnaker\",\"doi\":\"10.1109/CVPRW.2003.10035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a new Hidden Markov Model with time-dependent states. Estimation of this model is shown to be as fast and easy as the estimation of regular HMMs. We demonstrate the usefulness and feasibility of such time-dependent HMMs with an application in which illegitimate access to personnel-only rooms in airports etc. can be distinguished from access by legitimate personnel, based on differences in the time of access or differences in the motion trajectories.\",\"PeriodicalId\":121249,\"journal\":{\"name\":\"2003 Conference on Computer Vision and Pattern Recognition Workshop\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2003 Conference on Computer Vision and Pattern Recognition Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPRW.2003.10035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 Conference on Computer Vision and Pattern Recognition Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2003.10035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time-dependent HMMs for visual intrusion detection
We propose a new Hidden Markov Model with time-dependent states. Estimation of this model is shown to be as fast and easy as the estimation of regular HMMs. We demonstrate the usefulness and feasibility of such time-dependent HMMs with an application in which illegitimate access to personnel-only rooms in airports etc. can be distinguished from access by legitimate personnel, based on differences in the time of access or differences in the motion trajectories.
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