{"title":"Principal Gabor filters for face recognition","authors":"V. Štruc, Rok Gajsek, N. Pavesic","doi":"10.1109/BTAS.2009.5339020","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339020","url":null,"abstract":"Gabor filters have proven themselves to be a powerful tool for facial feature extraction. An abundance of recognition techniques presented in the literature exploits these filters to achieve robust face recognition. However, while exhibiting desirable properties, such as orientational selectivity or spatial locality, Gabor filters have also some shortcomings which crucially affect the characteristics and size of the Gabor representation of a given face pattern. Amongst these shortcomings the fact that the filters are not orthogonal one to another and are, hence, correlated is probably the most important. This makes the information contained in the Gabor face representation redundant and also affects the size of the representation. To overcome this problem we propose in this paper to employ orthonormal linear combinations of the original Gabor filters rather than the filters themselves for deriving the Gabor face representation. The filters, named principal Gabor filters for the fact that they are computed by means of principal component analysis, are assessed in face recognition experiments performed on the XM2VTS and YaleB databases, where encouraging results are achieved.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121634081","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":"GREYC keystroke: A benchmark for keystroke dynamics biometric systems","authors":"R. Giot, Mohamad El-Abed, C. Rosenberger","doi":"10.1109/BTAS.2009.5339051","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339051","url":null,"abstract":"Even if the market penetration rate of biometric technologies is still far below its potential, many biometric systems are used in our daily real-life. One of the main reasons to its low proliferation is the lack of a generic and complete approach that quantifies the performance of biometric systems taking into account individuals' perception among the process. Among all the existing biometric modalities, authentication systems based on keystroke dynamics are particularly interesting. Many researchers proposed in the last decades some algorithms to increase the efficiency of this approach. Nevertheless, none significant benchmark is available and commonly used in the state of the art to compare them by using a similar and rigorous protocol. We propose in this paper: a benchmark testing suite composed of a database and a software that are available for the scientific community for the evaluation of keystroke dynamics based systems. Performance evaluation of various keystroke dynamics methods tested on the database is available in [1].","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133504146","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":"Exploiting the “doddington zoo” effect in biometric fusion","authors":"A. Ross, A. Rattani, M. Tistarelli","doi":"10.1109/BTAS.2009.5339011","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339011","url":null,"abstract":"Recent research in biometrics has suggested the existence of the “Biometric Menagerie” in which weak users contribute disproportionately to the error rate (FAR and FRR) of a biometric system. The aim of this work is to utilize this observation to design a multibiometric system where information is consolidated on a user-specific basis. To facilitate this, the users in a database are characterized into multiple categories and only users belonging to weak categories are required to provide additional biometric information. The contribution of this work lies in (a) the design of a selective fusion scheme where fusion is invoked only for a subset of users, and (b) evaluating the performance of such a scheme on two public datasets. Experiments on the multi-unit CASIA V3 iris database and multi-unit WVU fingerprint database indicate that selective fusion, as defined in this work, improves overall matching accuracy while potentially reducing overall computational time. This has positive implications in a large-scale system where the throughput can be substantially increased without compromising the verification accuracy of the system.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129422930","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":"Online learning in biometrics: A case study in face classifier update","authors":"Richa Singh, Mayank Vatsa, A. Ross, A. Noore","doi":"10.1109/BTAS.2009.5339071","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339071","url":null,"abstract":"In large scale applications, hundreds of new subjects may be regularly enrolled in a biometric system. To account for the variations in data distribution caused by these new enrollments, biometric systems require regular re-training which usually results in a very large computational overhead. This paper formally introduces the concept of online learning in biometrics. We demonstrate its application in classifier update algorithms to re-train classifier decision boundaries. Specifically, the algorithm employs online learning technique in a 2ν-Granular Soft Support Vector Machine for rapidly training and updating face recognition systems. The proposed online classifier is used in a face recognition application for classifying genuine and impostor match scores impacted by different covariates. Experiments on a heterogeneous face database of 1,194 subjects show that the proposed online classifier not only improves the verification accuracy but also significantly reduces the computational cost.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133107903","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":"Alphabetical list of titles","authors":"Danse de Buffons","doi":"10.1109/btas.2009.5339007","DOIUrl":"https://doi.org/10.1109/btas.2009.5339007","url":null,"abstract":"","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115634926","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":"BTAS'09 organizing committee","authors":"M. Abdel-Mottaleb, K. Bowyer","doi":"10.1109/btas.2009.5339086","DOIUrl":"https://doi.org/10.1109/btas.2009.5339086","url":null,"abstract":"","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133868039","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":"General chair's welcome to BTAS 2009","authors":"","doi":"10.1109/btas.2009.5339008","DOIUrl":"https://doi.org/10.1109/btas.2009.5339008","url":null,"abstract":"","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126156046","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}