LEADER 03935nam 22005655 450 001 9910349278703321 005 20200701220834.0 010 $a3-030-26972-8 024 7 $a10.1007/978-3-030-26972-2 035 $a(CKB)4100000009362631 035 $a(DE-He213)978-3-030-26972-2 035 $a(MiAaPQ)EBC5900245 035 $a(PPN)260303879 035 $a(EXLCZ)994100000009362631 100 $a20190921d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSelfie Biometrics $eAdvances and Challenges /$fedited by Ajita Rattani, Reza Derakhshani, Arun Ross 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (IX, 380 p. 154 illus., 128 illus. in color.) 225 1 $aAdvances in Computer Vision and Pattern Recognition,$x2191-6586 311 $a3-030-26971-X 320 $aIncludes bibliographical references and index. 327 $a1. Introduction to Selfie Biometrics -- Part I: Selfie Finger, Ocular and Face Biometrics -- 2. User Authentication via Finger-selfies -- 3. A Scheme for Fingerphoto Recognition in Smartphones -- 4. MICHE Competitions: A Realistic Experience with Uncontrolled Eye Region Acquisition -- 5. Super-Resolution for Selfie Biometrics: Introduction and Application to Face and Iris -- 6. Foveated Vision for Biologically-inspired Continuous face Authentication. 330 $aThis book highlights the field of selfie biometrics, providing a clear overview and presenting recent advances and challenges. It also discusses numerous selfie authentication techniques on mobile devices. Biometric authentication using mobile devices is becoming a convenient and important means of verifying identity for secured access and services such as telebanking and electronic transactions. In this context, face and ocular biometrics in the visible spectrum has gained increased attention from the research community. However, device mobility and operation in uncontrolled environments mean that facial and ocular images captured with mobile devices exhibit substantial degradation as a result of adverse lighting conditions, specular reflections and motion and defocus blur. In addition, low spatial resolution and the small sensor of front-facing mobile cameras further degrade the sample quality, reducing the recognition accuracy of face and ocular recognition technology when integrated into smartphones. Presenting the state of the art in mobile biometric research and technology, and offering an overview of the potential problems in real-time integration of biometrics in mobile devices, this book is a valuable resource for final-year undergraduate students, postgraduate students, engineers, researchers and academics in various fields of computer engineering. 410 0$aAdvances in Computer Vision and Pattern Recognition,$x2191-6586 606 $aBiometry 606 $aUser interfaces (Computer systems) 606 $aBiometrics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22040 606 $aUser Interfaces and Human Computer Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/I18067 615 0$aBiometry. 615 0$aUser interfaces (Computer systems) 615 14$aBiometrics. 615 24$aUser Interfaces and Human Computer Interaction. 676 $a570.15195 676 $a006.248 702 $aRattani$b Ajita$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDerakhshani$b Reza$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRoss$b Arun$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349278703321 996 $aSelfie Biometrics$92533134 997 $aUNINA