{"title":"在线隐私安全参与跟踪系统","authors":"Cheng Zhang, Cheng Chang, L. Chen, Yang Liu","doi":"10.1145/3242969.3266295","DOIUrl":null,"url":null,"abstract":"Tracking learners' engagement is useful for monitoring their learning quality. With an increasing number of online video courses, a system that can automatically track learners' engagement is expected to significantly help in improving the outcomes of learners' study. In this demo, we show such a system to predict a user's engagement changes in real time. Our system utilizes webcams ubiquitously existing in nowadays computers, the face tracking function that runs inside the Web browsers to avoid sending learners' videos to the cloud, and a Python Flask web service. Our demo provides a solution of using mature technologies to provide real-time engagement monitoring with privacy protection.","PeriodicalId":308751,"journal":{"name":"Proceedings of the 20th ACM International Conference on Multimodal Interaction","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Online Privacy-Safe Engagement Tracking System\",\"authors\":\"Cheng Zhang, Cheng Chang, L. Chen, Yang Liu\",\"doi\":\"10.1145/3242969.3266295\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tracking learners' engagement is useful for monitoring their learning quality. With an increasing number of online video courses, a system that can automatically track learners' engagement is expected to significantly help in improving the outcomes of learners' study. In this demo, we show such a system to predict a user's engagement changes in real time. Our system utilizes webcams ubiquitously existing in nowadays computers, the face tracking function that runs inside the Web browsers to avoid sending learners' videos to the cloud, and a Python Flask web service. Our demo provides a solution of using mature technologies to provide real-time engagement monitoring with privacy protection.\",\"PeriodicalId\":308751,\"journal\":{\"name\":\"Proceedings of the 20th ACM International Conference on Multimodal Interaction\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 20th ACM International Conference on Multimodal Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3242969.3266295\",\"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 20th ACM International Conference on Multimodal Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3242969.3266295","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tracking learners' engagement is useful for monitoring their learning quality. With an increasing number of online video courses, a system that can automatically track learners' engagement is expected to significantly help in improving the outcomes of learners' study. In this demo, we show such a system to predict a user's engagement changes in real time. Our system utilizes webcams ubiquitously existing in nowadays computers, the face tracking function that runs inside the Web browsers to avoid sending learners' videos to the cloud, and a Python Flask web service. Our demo provides a solution of using mature technologies to provide real-time engagement monitoring with privacy protection.
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