D. Datcu, Marina-Anca Cidotã, S. Lukosch, L. Rothkrantz
{"title":"基于特定面部区域的可见光谱非接触自动心率分析","authors":"D. Datcu, Marina-Anca Cidotã, S. Lukosch, L. Rothkrantz","doi":"10.1145/2516775.2516805","DOIUrl":null,"url":null,"abstract":"The current paper presents a comparative study on the influence of different face regions for contactless extraction of the heart rate by computer vision in visible spectrum. A second novelty of our research is the use of Active Appearance Models for computing the shape of the face and of the facial features. Following an experimental setup, we determine that forehead and cheek face regions are more relevant for computing the heart rate. This outcome leads to an optimized face scanning method, faster processing times and better pulse detection results. The findings were implemented in an automatic system prototype for noncontact face analysis. Our methods were tested and validated using video recordings of people in laboratory setup.","PeriodicalId":316788,"journal":{"name":"International Conference on Computer Systems and Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":"{\"title\":\"Noncontact automatic heart rate analysis in visible spectrum by specific face regions\",\"authors\":\"D. Datcu, Marina-Anca Cidotã, S. Lukosch, L. Rothkrantz\",\"doi\":\"10.1145/2516775.2516805\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The current paper presents a comparative study on the influence of different face regions for contactless extraction of the heart rate by computer vision in visible spectrum. A second novelty of our research is the use of Active Appearance Models for computing the shape of the face and of the facial features. Following an experimental setup, we determine that forehead and cheek face regions are more relevant for computing the heart rate. This outcome leads to an optimized face scanning method, faster processing times and better pulse detection results. The findings were implemented in an automatic system prototype for noncontact face analysis. Our methods were tested and validated using video recordings of people in laboratory setup.\",\"PeriodicalId\":316788,\"journal\":{\"name\":\"International Conference on Computer Systems and Technologies\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"37\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computer Systems and Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2516775.2516805\",\"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 Conference on Computer Systems and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2516775.2516805","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noncontact automatic heart rate analysis in visible spectrum by specific face regions
The current paper presents a comparative study on the influence of different face regions for contactless extraction of the heart rate by computer vision in visible spectrum. A second novelty of our research is the use of Active Appearance Models for computing the shape of the face and of the facial features. Following an experimental setup, we determine that forehead and cheek face regions are more relevant for computing the heart rate. This outcome leads to an optimized face scanning method, faster processing times and better pulse detection results. The findings were implemented in an automatic system prototype for noncontact face analysis. Our methods were tested and validated using video recordings of people in laboratory setup.