{"title":"基于计算机视觉的微笑识别与分类","authors":"Ramya Rao, Veena N Hedge","doi":"10.1109/ICAITPR51569.2022.9844198","DOIUrl":null,"url":null,"abstract":"A simple method for the recognition and classification of varied types of smiles using the basics of machine learning is proposed in this paper. Machine-human interaction has seen exponential growth in the last decade. Key features of this interaction include emotion detection. A smiling face is often considered a sign of euphoria and excitement. The analysis is performed on real-time video sequence. The algorithm used for detection is a 68-point facial landmark recognition with aspect ratio calculation of facial features such as mouth and eyes.","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recognition and Classification of Smiles using Computer Vision\",\"authors\":\"Ramya Rao, Veena N Hedge\",\"doi\":\"10.1109/ICAITPR51569.2022.9844198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A simple method for the recognition and classification of varied types of smiles using the basics of machine learning is proposed in this paper. Machine-human interaction has seen exponential growth in the last decade. Key features of this interaction include emotion detection. A smiling face is often considered a sign of euphoria and excitement. The analysis is performed on real-time video sequence. The algorithm used for detection is a 68-point facial landmark recognition with aspect ratio calculation of facial features such as mouth and eyes.\",\"PeriodicalId\":262409,\"journal\":{\"name\":\"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAITPR51569.2022.9844198\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAITPR51569.2022.9844198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition and Classification of Smiles using Computer Vision
A simple method for the recognition and classification of varied types of smiles using the basics of machine learning is proposed in this paper. Machine-human interaction has seen exponential growth in the last decade. Key features of this interaction include emotion detection. A smiling face is often considered a sign of euphoria and excitement. The analysis is performed on real-time video sequence. The algorithm used for detection is a 68-point facial landmark recognition with aspect ratio calculation of facial features such as mouth and eyes.