{"title":"使用抽象隐马尔可夫模型利用注视行为推断任务转移","authors":"D. Gamarra","doi":"10.4114/INTARTIF.VOL19ISS58PP1-16","DOIUrl":null,"url":null,"abstract":"We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations.","PeriodicalId":176050,"journal":{"name":"Inteligencia Artif.","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Utilizing Gaze Behavior for Inferring Task Transitions Using Abstract Hidden Markov Models\",\"authors\":\"D. Gamarra\",\"doi\":\"10.4114/INTARTIF.VOL19ISS58PP1-16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations.\",\"PeriodicalId\":176050,\"journal\":{\"name\":\"Inteligencia Artif.\",\"volume\":\"127 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Inteligencia Artif.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4114/INTARTIF.VOL19ISS58PP1-16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Inteligencia Artif.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4114/INTARTIF.VOL19ISS58PP1-16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Utilizing Gaze Behavior for Inferring Task Transitions Using Abstract Hidden Markov Models
We demonstrate an improved method for utilizing observed gaze behavior and show that it is useful in inferring hand movement intent during goal directed tasks. The task dynamics and the relationship between hand and gaze behavior are learned using an Abstract Hidden Markov Model (AHMM). We show that the predicted hand movement transitions occur consistently earlier in AHMM models with gaze than those models that do not include gaze observations.
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