Shu Zhang, Danhuai Guo, Ying-tieng Zhu, Deqiang Wang
{"title":"浩瀚挑战2017:迷你挑战1","authors":"Shu Zhang, Danhuai Guo, Ying-tieng Zhu, Deqiang Wang","doi":"10.1109/VAST.2017.8585461","DOIUrl":null,"url":null,"abstract":"In this paper, we addressed the mini-challenge I. To efficiently identify odd behaviors and general patterns, visual analytics was used to parse trajectory data of vehicles and support spatial analyses. Firstly, the adjacent relations among spatial objects were extracted and then simplified as a topological graph. Base on the topological representation, cluster methods and spatio-temporal visualization were utilized to conduct a comprehensive analysis. Through visual analytics on the topological graph, we found general and regular behavior patterns of passages in the preserve and recognize outliers that reflected odd behaviors.","PeriodicalId":149607,"journal":{"name":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"VAST Challenge 2017: Mini-challenge 1\",\"authors\":\"Shu Zhang, Danhuai Guo, Ying-tieng Zhu, Deqiang Wang\",\"doi\":\"10.1109/VAST.2017.8585461\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we addressed the mini-challenge I. To efficiently identify odd behaviors and general patterns, visual analytics was used to parse trajectory data of vehicles and support spatial analyses. Firstly, the adjacent relations among spatial objects were extracted and then simplified as a topological graph. Base on the topological representation, cluster methods and spatio-temporal visualization were utilized to conduct a comprehensive analysis. Through visual analytics on the topological graph, we found general and regular behavior patterns of passages in the preserve and recognize outliers that reflected odd behaviors.\",\"PeriodicalId\":149607,\"journal\":{\"name\":\"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VAST.2017.8585461\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VAST.2017.8585461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we addressed the mini-challenge I. To efficiently identify odd behaviors and general patterns, visual analytics was used to parse trajectory data of vehicles and support spatial analyses. Firstly, the adjacent relations among spatial objects were extracted and then simplified as a topological graph. Base on the topological representation, cluster methods and spatio-temporal visualization were utilized to conduct a comprehensive analysis. Through visual analytics on the topological graph, we found general and regular behavior patterns of passages in the preserve and recognize outliers that reflected odd behaviors.