Pallav Borisagar, Smeet Jani, Yash Agrawal, R. Parekh
{"title":"高效紧凑的人脸识别技术综述","authors":"Pallav Borisagar, Smeet Jani, Yash Agrawal, R. Parekh","doi":"10.1109/sceecs48394.2020.143","DOIUrl":null,"url":null,"abstract":"Face detection deals with the specified object(face) within the given database. Several algorithms have been de-fined by different researchers for face recognition. Research, technology advancement and applications incorporating face recognition over the last few decades have grown enormously. It is growing as one of the profound and exciting research fields. Some of the practical and efficient algorithms for face recognition are Principal Component Analysis (PCA), Artificial Neural Network (ANN), Support Vector Machine (SVM), Feature based approach, Gabor wavelet, GPU based approach, 3D model-based face recognition, Linear Discriminant Analysis (LDA) and Using Facial Symmetry. Face recognition is a multidimensional field. Different algorithms give different performances in different situations like illumination, noise, pose and disgiuse change. All the aforementioned techniques are described briefly in this paper so as to give the general idea. The main focus of the paper is to bring all the different techniques at the same place and make it easy to review them.","PeriodicalId":167175,"journal":{"name":"2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Efficient and Compact Review of Face Recognition Techniques\",\"authors\":\"Pallav Borisagar, Smeet Jani, Yash Agrawal, R. Parekh\",\"doi\":\"10.1109/sceecs48394.2020.143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Face detection deals with the specified object(face) within the given database. Several algorithms have been de-fined by different researchers for face recognition. Research, technology advancement and applications incorporating face recognition over the last few decades have grown enormously. It is growing as one of the profound and exciting research fields. Some of the practical and efficient algorithms for face recognition are Principal Component Analysis (PCA), Artificial Neural Network (ANN), Support Vector Machine (SVM), Feature based approach, Gabor wavelet, GPU based approach, 3D model-based face recognition, Linear Discriminant Analysis (LDA) and Using Facial Symmetry. Face recognition is a multidimensional field. Different algorithms give different performances in different situations like illumination, noise, pose and disgiuse change. All the aforementioned techniques are described briefly in this paper so as to give the general idea. The main focus of the paper is to bring all the different techniques at the same place and make it easy to review them.\",\"PeriodicalId\":167175,\"journal\":{\"name\":\"2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/sceecs48394.2020.143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/sceecs48394.2020.143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Efficient and Compact Review of Face Recognition Techniques
Face detection deals with the specified object(face) within the given database. Several algorithms have been de-fined by different researchers for face recognition. Research, technology advancement and applications incorporating face recognition over the last few decades have grown enormously. It is growing as one of the profound and exciting research fields. Some of the practical and efficient algorithms for face recognition are Principal Component Analysis (PCA), Artificial Neural Network (ANN), Support Vector Machine (SVM), Feature based approach, Gabor wavelet, GPU based approach, 3D model-based face recognition, Linear Discriminant Analysis (LDA) and Using Facial Symmetry. Face recognition is a multidimensional field. Different algorithms give different performances in different situations like illumination, noise, pose and disgiuse change. All the aforementioned techniques are described briefly in this paper so as to give the general idea. The main focus of the paper is to bring all the different techniques at the same place and make it easy to review them.