Zeno Albisser, M. Riegler, P. Halvorsen, Jiang Zhou, C. Griwodz, I. Balasingham, C. Gurrin
{"title":"Expert driven semi-supervised elucidation tool for medical endoscopic videos","authors":"Zeno Albisser, M. Riegler, P. Halvorsen, Jiang Zhou, C. Griwodz, I. Balasingham, C. Gurrin","doi":"10.1145/2713168.2713184","DOIUrl":null,"url":null,"abstract":"In this paper, we present a novel application for elucidating all kind of videos that require expert knowledge, e.g., sport videos, medical videos etc., focusing on endoscopic surgery and video capsule endoscopy. In the medical domain, the knowledge of experts for tagging and interpretation of videos is of high value. As a result of the stressful working environment of medical doctors, they often simply do not have time for extensive annotations. We therefore present a semi-supervised method to gather the annotations in a very easy and time saving way for the experts and we show how this information can be used later on.","PeriodicalId":202494,"journal":{"name":"Proceedings of the 6th ACM Multimedia Systems Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th ACM Multimedia Systems Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2713168.2713184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
In this paper, we present a novel application for elucidating all kind of videos that require expert knowledge, e.g., sport videos, medical videos etc., focusing on endoscopic surgery and video capsule endoscopy. In the medical domain, the knowledge of experts for tagging and interpretation of videos is of high value. As a result of the stressful working environment of medical doctors, they often simply do not have time for extensive annotations. We therefore present a semi-supervised method to gather the annotations in a very easy and time saving way for the experts and we show how this information can be used later on.