Kevin O'Connor, G. Hales, Jonathan Hight, S. Modi, S. Elliott
{"title":"Comparison of face image quality metrics: Electronic and legacy mug shots","authors":"Kevin O'Connor, G. Hales, Jonathan Hight, S. Modi, S. Elliott","doi":"10.1109/CIBIM.2011.5949219","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949219","url":null,"abstract":"Automated face recognition offers an effective method for identifying individuals. Face images have been used in a number of different applications, including driver's licenses, passports and identification cards. To provide some form of standardization for photographs in these applications, ISO / IEC JTC 1 SC 37 have developed standardized data interchange formats to promote interoperability. There are many different publically available face databases available to the research community that are used to advance the field of face recognition algorithms, amongst other uses. In this paper, we examine how an existing database that has been used extensively in research (FERET) compares with two operational data sets with respect to some of the metrics outlined in the standard ISO / IEC 19794-5. The goals of this research are to provide the community with a comparison of a baseline data set and to compare this baseline to a photographic data set that has been scanned in from mug-shot photographs, as well as a data set of digitally captured photographs. It is hoped that this information will provide Face Recognition System (FRS) developers some guidance on the characteristics of operationally collected data sets versus a controlled-collection database.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128980699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tamirat T. Abegaz, G. Dozier, Kelvin S. Bryant, Joshua Adams, Khary Popplewell, Joseph Shelton, K. Ricanek, D. Woodard
{"title":"Hybrid GAs for Eigen-based facial recognition","authors":"Tamirat T. Abegaz, G. Dozier, Kelvin S. Bryant, Joshua Adams, Khary Popplewell, Joseph Shelton, K. Ricanek, D. Woodard","doi":"10.1109/CIBIM.2011.5949209","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949209","url":null,"abstract":"In this paper, we have performed an evaluation of genetic-based feature selection and weighting on the PCA-based face recognition. This work highlights the first attempt of applying Genetic Algorithm (GA) based feature selection on the Eigenface method. The results show that genetic-based feature selection reduces the number of features needed by approximately 50% while improving the identification accuracy over the baseline. Genetic-based feature weighting significantly improves the accuracy from an 87.14% to a 92.5% correct recognition rate.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131816831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Dozier, Kamilah Purrington, Khary Popplewell, Joseph Shelton, Tamirat T. Abegaz, Kelvin S. Bryant, Joshua Adams, D. Woodard, Philip E. Miller
{"title":"GEFeS: Genetic & evolutionary feature selection for periocular biometric recognition","authors":"G. Dozier, Kamilah Purrington, Khary Popplewell, Joseph Shelton, Tamirat T. Abegaz, Kelvin S. Bryant, Joshua Adams, D. Woodard, Philip E. Miller","doi":"10.1109/CIBIM.2011.5949211","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949211","url":null,"abstract":"In this paper, we introduce the concept of genetic & evolutionary feature selection (GEFeS) for periocular biometric recognition. Our results show that GEFeS dramatically reduces the number of features needed for periocular recognition as well as increases recognition accuracy.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125803927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Consent biometrics","authors":"Kai Yang, Yingzi Du","doi":"10.1109/CIBIM.2011.5949207","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949207","url":null,"abstract":"Biometrics identifies/verifies a person using his/her physiological or behavioral characteristics. It is becoming an important ally for law enforcement and homeland security. However, there are some safety and privacy concerns: biometrics guarded system can be accessed when users are under threat, reluctant or even unconscious states. For future consumer biometric applications (such as biometric ATM machines or biometric credit cards), the biggest concern is user safety: criminals may intimidate or even hurt users to get into their accounts. In this paper, we propose a new concept, Consent Biometrics, which incorporates a consent signature into biometric systems. We introduce two schemes that can realize the Consent Biometrics idea and an example design for consent iris recognition. The proposed consent biometrics can not only detect the willingness of users, but also improve recognition accuracy.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121800450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}