{"title":"基于分层和紧凑位图的人体动态数据可视化数据结构","authors":"H. Kimata, Wu Xiaojun, Ryuichi Tanida","doi":"10.1145/3406971.3406980","DOIUrl":null,"url":null,"abstract":"Analysis and prediction of human dynamics are key technologies to evolve various services for cognizing real world events, and they have been intensively studied in the field of data science. Technologies that support such studies have been advanced, in fields of sensing, analysis, and database. Thanks to recent sensing technologies, precision of sensing human movement is increasing, and a large amount of data is been generated continuously. Accordingly data that indicate a very large population can be efficiently collected, stored and visualized. To enable such a large amount of data to be visualized quickly, we propose data structure for two dimensional space data that has a compact one byte representation and hierarchical structure that can efficiently handle human dynamics data.","PeriodicalId":111905,"journal":{"name":"Proceedings of the 4th International Conference on Graphics and Signal Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Hierarchical and Compact Bitmap Based Data Structure of Human Dynamics Data for Visualization\",\"authors\":\"H. Kimata, Wu Xiaojun, Ryuichi Tanida\",\"doi\":\"10.1145/3406971.3406980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analysis and prediction of human dynamics are key technologies to evolve various services for cognizing real world events, and they have been intensively studied in the field of data science. Technologies that support such studies have been advanced, in fields of sensing, analysis, and database. Thanks to recent sensing technologies, precision of sensing human movement is increasing, and a large amount of data is been generated continuously. Accordingly data that indicate a very large population can be efficiently collected, stored and visualized. To enable such a large amount of data to be visualized quickly, we propose data structure for two dimensional space data that has a compact one byte representation and hierarchical structure that can efficiently handle human dynamics data.\",\"PeriodicalId\":111905,\"journal\":{\"name\":\"Proceedings of the 4th International Conference on Graphics and Signal Processing\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th International Conference on Graphics and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3406971.3406980\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Conference on Graphics and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3406971.3406980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hierarchical and Compact Bitmap Based Data Structure of Human Dynamics Data for Visualization
Analysis and prediction of human dynamics are key technologies to evolve various services for cognizing real world events, and they have been intensively studied in the field of data science. Technologies that support such studies have been advanced, in fields of sensing, analysis, and database. Thanks to recent sensing technologies, precision of sensing human movement is increasing, and a large amount of data is been generated continuously. Accordingly data that indicate a very large population can be efficiently collected, stored and visualized. To enable such a large amount of data to be visualized quickly, we propose data structure for two dimensional space data that has a compact one byte representation and hierarchical structure that can efficiently handle human dynamics data.