{"title":"一种用于活动检测可视化的交互式方法","authors":"Li Liu, S. Ozer, K. Bemis, Jay Takle, D. Silver","doi":"10.1109/LDAV.2013.6675173","DOIUrl":null,"url":null,"abstract":"Visualizing each time step in an activity from a scientific dataset can aid in understanding the data and phenomena. In this work, we present a Graphical User Interface (GUI) that allows scientists to first graphically model an activity, then detect any activities that match the model, and finally visualize the detected activities in time varying scientific data sets. As a graphical and state based interactive approach, an activity detection framework is implemented by our GUI as a tool for modelling, hypothesis-testing and searching for interested activities from the phenomena evolution of the data set. We demonstrate here some features of our GUI: a histogram is used to visualize the number of activities detected as a function of time and to allow the user to focus on a moment in time; a table is used to give details about the activities and the features participating in them; and finally the user is given the ability to click on the screen to bring up 3D images of the overall activity sequence, single time steps of an activity, or individual feature in an activity. We present examples from applications to two different data sets.","PeriodicalId":266607,"journal":{"name":"2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An interactive method for activity detection visualization\",\"authors\":\"Li Liu, S. Ozer, K. Bemis, Jay Takle, D. Silver\",\"doi\":\"10.1109/LDAV.2013.6675173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Visualizing each time step in an activity from a scientific dataset can aid in understanding the data and phenomena. In this work, we present a Graphical User Interface (GUI) that allows scientists to first graphically model an activity, then detect any activities that match the model, and finally visualize the detected activities in time varying scientific data sets. As a graphical and state based interactive approach, an activity detection framework is implemented by our GUI as a tool for modelling, hypothesis-testing and searching for interested activities from the phenomena evolution of the data set. We demonstrate here some features of our GUI: a histogram is used to visualize the number of activities detected as a function of time and to allow the user to focus on a moment in time; a table is used to give details about the activities and the features participating in them; and finally the user is given the ability to click on the screen to bring up 3D images of the overall activity sequence, single time steps of an activity, or individual feature in an activity. We present examples from applications to two different data sets.\",\"PeriodicalId\":266607,\"journal\":{\"name\":\"2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LDAV.2013.6675173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LDAV.2013.6675173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An interactive method for activity detection visualization
Visualizing each time step in an activity from a scientific dataset can aid in understanding the data and phenomena. In this work, we present a Graphical User Interface (GUI) that allows scientists to first graphically model an activity, then detect any activities that match the model, and finally visualize the detected activities in time varying scientific data sets. As a graphical and state based interactive approach, an activity detection framework is implemented by our GUI as a tool for modelling, hypothesis-testing and searching for interested activities from the phenomena evolution of the data set. We demonstrate here some features of our GUI: a histogram is used to visualize the number of activities detected as a function of time and to allow the user to focus on a moment in time; a table is used to give details about the activities and the features participating in them; and finally the user is given the ability to click on the screen to bring up 3D images of the overall activity sequence, single time steps of an activity, or individual feature in an activity. We present examples from applications to two different data sets.