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Biometric Recognition : 14th Chinese Conference, CCBR 2019, Zhuzhou, China, October 12–13, 2019, Proceedings / / edited by Zhenan Sun, Ran He, Jianjiang Feng, Shiguang Shan, Zhenhua Guo



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Titolo: Biometric Recognition : 14th Chinese Conference, CCBR 2019, Zhuzhou, China, October 12–13, 2019, Proceedings / / edited by Zhenan Sun, Ran He, Jianjiang Feng, Shiguang Shan, Zhenhua Guo Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Edizione: 1st ed. 2019.
Descrizione fisica: 1 online resource (XVI, 521 p.)
Disciplina: 006.4
570.15195
Soggetto topico: Biometrics (Biology)
Optical data processing
Artificial intelligence
Computer organization
User interfaces (Computer systems)
Computer security
Biometrics
Image Processing and Computer Vision
Artificial Intelligence
Computer Systems Organization and Communication Networks
User Interfaces and Human Computer Interaction
Systems and Data Security
Persona (resp. second.): SunZhenan
HeRan
FengJianjiang
ShanShiguang
GuoZhenhua
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Hand-Based Biometrics -- Local Discriminative Direction Extraction for Palmprint Recognition -- Fingerprint Presentation Attack Detection via Analyzing Fingerprint Pairs -- Finger Vein Recognition Based on Double-Orientation Coding Histogram -- Fingerprint Classification Based on Lightweighyt Neural Networks -- 3D Fingerprint Gender Classification Using Deep Learning -- A Novel Method for Finger Vein Recognition -- Rolled Fingerprint Mosaicking Algorithm Based on Block Scale -- Study and Realization of Partial Fingerprint Mosaicking Technology for Mobile Devices -- Gesture, Gait and Action -- Multiscale Temporal Network for Video-based Gait Recognition -- Global and Local Spatial-Attention Network for Isolated Gesture Recognition -- Authentication System Design Based On Dynamic Hand Gesture -- Feature Extraction and Classification Theory -- Structure Feature Learning: Constructing Functional Connectivity Network for Alzheimer’s disease Identification and Analysis -- Weakly Supervised Learning of Image Emotion Analysis Based on Cross-spatial Pooling -- Embarrassingly Easy Zero-Shot Image Recognition -- On the Generalization of GAN Image Forensics -- Face -- Deep Residual Equivariant Mapping for Multi-Angle Face Recognition -- The Impact of Data Correlation on Identification of Computer-Generated Face Images -- Face Image Deblurring Based on Iterative Spiral Optimization -- AdaptiveNet: Toward an Efficient Face Alignment Algorithm -- Cross-dimension Transfer Learning for Video-based Facial Expression Recognition -- Exploring Shape Deformation in 2D Images for Facial Expression Recognition -- Facial attractiveness prediction by Deep Adaptive Label Distribution Learning -- LWFD:A Simple Light-Weight Network for Face Detection -- Dairy Cow Tiny Face Recognition Based on Convolutional Neural Networks -- Reconstructed Face Recognition -- A Two-Stage Method for Assessing Facial Paralysis Severity by Fusing Multiple Classifiers -- Latent Spatial Features Based on Generative Adversarial Networks for Face Anti-spoofing -- Similarity Measurement between Reconstructed 3D Face and 2D Face based on Deep Learning -- Real-time Face Occlusion Recognition Algorithm Based on Feature Fusion -- Joint Face Detection and Alignment Using Focal Loss-based Multi-task Convolutional Neural Networks -- A Face Recognition Workflow Based upon Similarity Measurement -- 106-Point Facial Landmark Localization with Mobile Networks Based on Regression -- Eye-Based Biometrics -- Long Range Pupil Location Algorithm Based on the Improved Circle Fitting Method -- Multi-source heterogeneous iris recognition using Locality Preserving Projection -- Iris Recognition Based on Adaptive Optimization Log-Gabor Filter and RBF Neural Network -- Retinal vessel segmentation method based on improved deep U-net -- Multi-pyramid Optimized Mask R-CNN for Iris Detection and Segmentation -- Constrained Sequence Iris Quality Evaluation Based on Causal Relationship Decision Reasoning -- Iris Image Super Resolution based on GANs with Adversarial Triplets -- SDItg-Diff: Noisy Iris Localization based on Statistical Denoising -- End to end robust recognition method for iris using a dense deep convolutional neural network -- Emerging Biometrics -- X-Ray Image With Prohibited Items Synthesis Based on Generative Adversarial Network -- A Deep learning Approach to Web Bot Detection Using Mouse Behavioral Biometrics -- Multi-task Deep Learning for Child Gender and Age Determination on Hand Radiographs -- Shoe Pattern Recognition: A Benchmark -- Learning Discriminative Representation for ECG Biometrics Based on Multi-Scale 1D-PDV -- Off-line handwritten signature recognition based on discrete curvelet transform -- Research on automatic classification method of footwear under low resolution condition -- Behavioral Biometrics -- Low-resolution Person Re-identification By a Discriminative Resolution-invariant Network -- DHML: Deep Heterogeneous Metric Learning for VIS-NIR Person Re-identification -- Teager Energy Operator based Features with x-vector for Replay Attack Detection -- Video Human Behaviour Recognition Based on Improved SVM KNN for Traceability of Planting Industry -- Application of Unscented Kalman Filter in Tracking of Video Moving Target -- Similarity Scores based Re-Classification for Open-Set Person Re-Identification -- The GMM and I-vector Systems Based on Spoofing Algorithms for Speaker Spoofing Detection -- Feature Enhancement for Joint Human and Head Detection. .
Sommario/riassunto: The LNCS volume 11818 constitutes the proceedings of the 14th Chinese Conference on Biometric Recognition, held in Zhuzhou, China, in October 2019. The 56 papers presented in this book were carefully reviewed and selected from 74 submissions. The papers cover a wide range of topics such as face recognition and analysis; hand-based biometrics; eye-based biometrics; gesture, gait, and action; emerging biometrics; feature extraction and classification theory; and behavioral biometrics.
Titolo autorizzato: Biometric Recognition  Visualizza cluster
ISBN: 3-030-31456-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910349276603321
Lo trovi qui: Univ. Federico II
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Serie: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 11818