posted by user: vitos || 3043 views || tracked by 5 users: [display]

SI UER 2017 : IET Biometrics Special issue on Unconstrained Ear Recognition

FacebookTwitterLinkedInGoogle

Link: http://luks.fe.uni-lj.si/nluks/wp-content/uploads/2017/01/IET-BMT-Template.pdf
 
When Jul 1, 2017 - Sep 1, 2017
Where Europe
Submission Deadline Sep 1, 2017
Notification Due Apr 3, 2017
Final Version Due May 1, 2017
Categories    biometrics   computer vision   ear recognition   special issue
 

Call For Papers

** CALL FOR PAPERS **

IET Biometrics Special Issue on
UNCONSTRAINED EAR RECOGNITION


** Motivation **
Despite the numerous application possibilities in security, surveillance applications, forensics, criminal investigations or border control, the existing research in ear recognition has seldom gone beyond laboratory settings. This can mostly be attributed to the enormous appearance variability of ear images when captured in unconstrained settings. However, due to recent advances in computer vision, machine learning and artificial intelligence (e.g. with deep learning), many recognition problems are now solvable in unconstrained settings and many biometric modalities (including ear images) that were commonly too complex for real-life deployment are now becoming a viable source of data for identity recognition.

The goal of this special issue is to present the most advanced and up-to-date work related to unconstrained ear recognition, report recent findings and make fundamental and/or empirical contributions to the field. The special issue is meant to reflect the current state of technology in the area of ear recognition and serve as a reference for researchers working on problems relevant to ear-recognition technology.

** Topics of Interest **
We solicit original high-quality papers on various topics related to ear recognition in unconstrained settings. Authors of submitted papers are requested to clearly explain how their work contributes to the field. Topics of interest include, but are not limited to:
• Pre-processing techniques for ear recognition
• Normalization techniques for ear recognition
• Ear recognition in unconstrained settings
• Ear detection/segmentation/localization techniques
• Ear recognition with different modalities (2D, 3D, IR, NIS, ear-prints, heterogeneous)
• Machine learning techniques for ear recognition
• Elimination of influence of covariate factors
• Context-aware ear recognition and detection
• Fusion techniques involving ear images
• Individuality models/studies for ear recognition
• Scalability studies for ear recognition technology
• New datasets and performance evaluations
• Overviews and surveys related to ear recognition
• Related applications (e.g., in forensics).

All submissions will undergo a rigorous review process conducted by experts in the field.

** Important Dates **
Submission deadline: September 1st, 2017
Author notification: April 3rd, 2018
Target publication date: May, 2018

** Guest Editors **
Peter Peer, University of Ljubljana, Slovenia
Vitomir Štruc, University of Ljubljana, Slovenia

Related Resources

ICPR-IETBiom-VSaaS 2021   25th ICPR Special Issue on Real-Time Visual Surveillance as-a-Service (VSaaS) for Smart Security Solutions in IET Biometrics
CCVPR 2020   2020 3rd International Joint Conference on Computer Vision and Pattern Recognition (CCVPR 2020)
SI:ICPR-MVAP 2021   Special Issue on Selected Papers from 25th ICPR in Machine Vision and Applications
ICRMV--EI, Scopus 2021   2021 The 5th International Conference on Robotics and Machine Vision (ICRMV 2021)--Ei Compendex, Scopus
WMWB 2020   TC4 Workshop on Mobile and Wearable Biometrics Workshop
VISAPP 2021   16th International Conference on Computer Vision Theory and Applications
IET-JoE SI on Grid Resilience 2020   Special Issue on “Engineering Techniques & Technologies to Enhance Power System Resilience” - IET The Journal of Engineering
CBDA 2021   2nd International Conference on Big Data
PRIS-SCOPUS 2021   3rd International Conference on Pattern Recognition and Intelligent Systems (PRIS 2021)
SI BIOFOR 2020   Special Issue on Advances in Digital Security: Biometrics and Forensics (BIOFOR)