{"title":"基于图像挖掘方法的交通/人员行为知识发现","authors":"F. Safara, A. Eftekhari-Moghadam","doi":"10.1109/GMAI.2006.31","DOIUrl":null,"url":null,"abstract":"The increasing number of image archives has made image mining an important task because of its potential to discover useful image patterns and relationships from a large set of images. We proposed a framework for extracting knowledge from a sequence of images. The structure of the framework composed of two modules: image analysis and knowledge processing. In this paper, we customized the knowledge-processing module for checking normality/abnormality of vehicles/people behaviors in each image sequence","PeriodicalId":438098,"journal":{"name":"Geometric Modeling and Imaging--New Trends (GMAI'06)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Knowledge Discovery of Traffic/People Behaviors Based on Image Mining Approach\",\"authors\":\"F. Safara, A. Eftekhari-Moghadam\",\"doi\":\"10.1109/GMAI.2006.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing number of image archives has made image mining an important task because of its potential to discover useful image patterns and relationships from a large set of images. We proposed a framework for extracting knowledge from a sequence of images. The structure of the framework composed of two modules: image analysis and knowledge processing. In this paper, we customized the knowledge-processing module for checking normality/abnormality of vehicles/people behaviors in each image sequence\",\"PeriodicalId\":438098,\"journal\":{\"name\":\"Geometric Modeling and Imaging--New Trends (GMAI'06)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geometric Modeling and Imaging--New Trends (GMAI'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GMAI.2006.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geometric Modeling and Imaging--New Trends (GMAI'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GMAI.2006.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Knowledge Discovery of Traffic/People Behaviors Based on Image Mining Approach
The increasing number of image archives has made image mining an important task because of its potential to discover useful image patterns and relationships from a large set of images. We proposed a framework for extracting knowledge from a sequence of images. The structure of the framework composed of two modules: image analysis and knowledge processing. In this paper, we customized the knowledge-processing module for checking normality/abnormality of vehicles/people behaviors in each image sequence
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