Tobias Zimmermann, Markus Weber, M. Liwicki, D. Stricker
{"title":"covid - a:基于笔的协作视频注释","authors":"Tobias Zimmermann, Markus Weber, M. Liwicki, D. Stricker","doi":"10.1145/2304496.2304506","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a pen-based annotation tool for videos. Annotating videos is an exhausting task, but it has a great benefit for several communities, as labeled ground truth data is the foundation for supervised machine learning approaches. Thus, there is need for an easy-to-use tool which assists users with labeling even complex structures. For outlining and labeling the shape of an object, we introduce a pen-based interface which combines pen and touch input. In our experiments we show that especially for complex structures the usage of a pen device improves the effectiveness of the outlining process.","PeriodicalId":196376,"journal":{"name":"International Workshop on Video and Image Ground Truth in Computer Vision Applications","volume":"51 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"CoVidA: pen-based collaborative video annotation\",\"authors\":\"Tobias Zimmermann, Markus Weber, M. Liwicki, D. Stricker\",\"doi\":\"10.1145/2304496.2304506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a pen-based annotation tool for videos. Annotating videos is an exhausting task, but it has a great benefit for several communities, as labeled ground truth data is the foundation for supervised machine learning approaches. Thus, there is need for an easy-to-use tool which assists users with labeling even complex structures. For outlining and labeling the shape of an object, we introduce a pen-based interface which combines pen and touch input. In our experiments we show that especially for complex structures the usage of a pen device improves the effectiveness of the outlining process.\",\"PeriodicalId\":196376,\"journal\":{\"name\":\"International Workshop on Video and Image Ground Truth in Computer Vision Applications\",\"volume\":\"51 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Video and Image Ground Truth in Computer Vision Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2304496.2304506\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Video and Image Ground Truth in Computer Vision Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2304496.2304506","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a pen-based annotation tool for videos. Annotating videos is an exhausting task, but it has a great benefit for several communities, as labeled ground truth data is the foundation for supervised machine learning approaches. Thus, there is need for an easy-to-use tool which assists users with labeling even complex structures. For outlining and labeling the shape of an object, we introduce a pen-based interface which combines pen and touch input. In our experiments we show that especially for complex structures the usage of a pen device improves the effectiveness of the outlining process.