Selfie biometrics : advances and challenges /: advances and challenges. (2019)

• Record Type: Book
• Further Information: Note: Ajita Rattani, Reza Derakhshani, Arun Ross, editors.
• Editors: Rattani, Ajita; Derakhshani, Reza; Ross, Arun A (Arun Abraham)
• Contents: Intro; Preface; Unique Features; Audience; Organization; Contents; About the Editors; 1 Introduction to Selfie Biometrics; 1.1 Mobile Biometrics; 1.2 Selfie Biometrics; 1.2.1 Types of Selfie Biometrics; 1.2.2 Selfie Biometrics and Spoof Attacks; 1.2.3 Selfie and Cloud-Based Services; 1.2.4 Selfie and Soft Biometrics; 1.3 Challenges and Future Directions; 1.4 Conclusion; References; Selfie Finger, Ocular and Face Biometrics; 2 User Authentication via Finger-Selfies; 2.1 Introduction; 2.2 Related Work; 2.2.1 Existing Databases; 2.2.2 Finger-Selfie Recognition Techniques 2.3 UNconstrained FingerPhoto (UNFIT) Dataset2.3.1 Database Acquisition; 2.3.2 Database Statistics; 2.3.3 Challenges; 2.3.4 Ground-Truth Annotation; 2.3.5 Experimental Protocol; 2.4 Segmentation Framework; 2.4.1 Segmentation Using VGG SegNet; 2.4.2 Implementation Details; 2.4.3 Performance Evaluation Metrics; 2.4.4 Segmentation Performance; 2.5 Finger-Selfie Recognition; 2.5.1 Feature Representations; 2.5.2 Finger-Selfie Recognition Performance; 2.6 Conclusion; References; 3 A Scheme for Fingerphoto Recognition in Smartphones; 3.1 Introduction; 3.2 Biometric Recognition Process 3.2.1 Acquisition3.2.2 Segmentation; 3.2.3 Enhancement; 3.2.4 Feature Extraction and Matching; 3.2.5 Quality Assessment; 3.2.6 Liveness Detection; 3.2.7 Mitigation of Nonidealities of Touchless Fingerprint Sensors; 3.3 Performance Analysis; 3.4 Conclusions; References; 4 MICHE Competitions: A Realistic Experience with Uncontrolled Eye Region Acquisition; 4.1 Introduction; 4.2 Iris Recognition and MICHE Challenges; 4.3 Challenge Setup and MICHE Dataset; 4.4 MICHE-I Challenge: Iris Segmentation; 4.4.1 Metrics Used to Evaluate the Segmentation Quality; 4.4.2 Methods Participating in MICHE-I 4.4.3 Some Interesting Notes on Achieved Results4.4.4 Recombination of Segmentation and Recognition Modules; 4.5 MICHE-II Challenge: Iris Recognition; 4.5.1 Methods Participating in MICHE-II; 4.5.2 Some Interesting Notes on Achieved Results; 4.6 MICHE After the Challenges; 4.7 Conclusions; References; 5 Super-resolution for Selfie Biometrics: Introduction and Application to Face and Iris; 5.1 Image Super-Resolution; 5.1.1 Reconstruction-Based Methods; 5.1.2 Learning-Based Methods; 5.1.3 Performance Metrics; 5.2 Face Super-Resolution; 5.2.1 Face Eigentransformation 5.2.2 Local Iterative Neighbour Embedding5.2.3 Linear Model of Coupled Sparse Support; 5.2.4 Results; 5.3 Iris Super-Resolution; 5.3.1 Iris Eigen-Patches; 5.3.2 Local Iterative Neighbour Embedding; 5.3.3 Results; 5.4 Summary and Future Trends; References; 6 Foveated Vision for Biologically Inspired Continuous Face Authentication; 6.1 Introduction; 6.2 Related Work; 6.3 Face Recognition on Mobile Devices; 6.3.1 Detection of the Face, Ocular Regions and the Landmarks; 6.3.2 Foveal and Peripheral Vision; 6.3.3 The Original HMAX Model; 6.3.4 Classification with the Softmax Layer
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2019
• Extent: 1 online resource (ix, 380 pages), illustrations (some color)
• Subjects: 006.2/48; Biometric identification; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030269722; 3030269728
• Related ISBNs: 9783030269715
• Notes: Note: Online resource; title from PDF title page (SpringerLink, viewed September 27, 2019).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.