{"title":"计算机视觉应用中图像数据集的高效标注","authors":"Julia Möhrmann, G. Heidemann","doi":"10.1145/2304496.2304498","DOIUrl":null,"url":null,"abstract":"High quality ground truth data sets are crucial for the development of image recognition systems. However, the task of annotating large image data sets manually takes a lot of time and effort. In order to lower the burden for the development of application-specific image recognition systems, we developed an advanced user interface. This interface is especially designed for non-expert users with little-to-no knowledge of computer vision techniques. The interface presents images clustered by similarity and allows for an efficient and simple annotation of large data sets. The integration of overview+detail concepts allows the precise navigation inside large data sets. The interface can be used without prior instructions on the underlying concepts, like self-organizing maps, image features or visualization techniques.","PeriodicalId":196376,"journal":{"name":"International Workshop on Video and Image Ground Truth in Computer Vision Applications","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Efficient annotation of image data sets for computer vision applications\",\"authors\":\"Julia Möhrmann, G. Heidemann\",\"doi\":\"10.1145/2304496.2304498\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High quality ground truth data sets are crucial for the development of image recognition systems. However, the task of annotating large image data sets manually takes a lot of time and effort. In order to lower the burden for the development of application-specific image recognition systems, we developed an advanced user interface. This interface is especially designed for non-expert users with little-to-no knowledge of computer vision techniques. The interface presents images clustered by similarity and allows for an efficient and simple annotation of large data sets. The integration of overview+detail concepts allows the precise navigation inside large data sets. The interface can be used without prior instructions on the underlying concepts, like self-organizing maps, image features or visualization techniques.\",\"PeriodicalId\":196376,\"journal\":{\"name\":\"International Workshop on Video and Image Ground Truth in Computer Vision Applications\",\"volume\":\"89 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"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/10.1145/2304496.2304498\",\"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/10.1145/2304496.2304498","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient annotation of image data sets for computer vision applications
High quality ground truth data sets are crucial for the development of image recognition systems. However, the task of annotating large image data sets manually takes a lot of time and effort. In order to lower the burden for the development of application-specific image recognition systems, we developed an advanced user interface. This interface is especially designed for non-expert users with little-to-no knowledge of computer vision techniques. The interface presents images clustered by similarity and allows for an efficient and simple annotation of large data sets. The integration of overview+detail concepts allows the precise navigation inside large data sets. The interface can be used without prior instructions on the underlying concepts, like self-organizing maps, image features or visualization techniques.