[visionlist] IET Biometrics SI [CFP]: Unconstrained Ear Recognition

Štruc, Vitomir Vitomir.Struc at fe.uni-lj.si
Fri Jul 28 01:58:09 -05 2017

** Apologies for cross-posting **

IET Biometrics (SCI 2016 IF: 1.382)

Submission deadline: 1 September 2017
Guest Editors: Vitomir Struc and Peter Peer

** 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).

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

** Submission Procedure **
All papers must be submitted through the journal’s Manuscript Central system:

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

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