{"title":"基于视觉的智能电视睡眠模式检测","authors":"Yeong Nam Chae, Suwon Lee, Byungok Han, H. Yang","doi":"10.1109/ICCE.2013.6486823","DOIUrl":null,"url":null,"abstract":"Sleep mode detection is one of the significant features of power management and green computing. However, for a television or a smart TV, it is difficult to detect a deactivation event because the user can use these devices without input from an input device. We propose a robust method to detect deactivation events based on a vision approach involving face detection and motion detection for a smart TV. Experiments are performed on a large dataset. The proposed approach significantly reduces false detections of faces and complement missed humans by means of motion detection.","PeriodicalId":6432,"journal":{"name":"2013 IEEE International Conference on Consumer Electronics (ICCE)","volume":"75 1","pages":"123-124"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Vision-based sleep mode detection for a smart TV\",\"authors\":\"Yeong Nam Chae, Suwon Lee, Byungok Han, H. Yang\",\"doi\":\"10.1109/ICCE.2013.6486823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sleep mode detection is one of the significant features of power management and green computing. However, for a television or a smart TV, it is difficult to detect a deactivation event because the user can use these devices without input from an input device. We propose a robust method to detect deactivation events based on a vision approach involving face detection and motion detection for a smart TV. Experiments are performed on a large dataset. The proposed approach significantly reduces false detections of faces and complement missed humans by means of motion detection.\",\"PeriodicalId\":6432,\"journal\":{\"name\":\"2013 IEEE International Conference on Consumer Electronics (ICCE)\",\"volume\":\"75 1\",\"pages\":\"123-124\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Consumer Electronics (ICCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE.2013.6486823\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Consumer Electronics (ICCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE.2013.6486823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sleep mode detection is one of the significant features of power management and green computing. However, for a television or a smart TV, it is difficult to detect a deactivation event because the user can use these devices without input from an input device. We propose a robust method to detect deactivation events based on a vision approach involving face detection and motion detection for a smart TV. Experiments are performed on a large dataset. The proposed approach significantly reduces false detections of faces and complement missed humans by means of motion detection.