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

** Apologies for cross-posting **

CALL FOR PAPERS
*************************************************
IET Biometrics Specal Issue on
UNCONSTRAINED EAR RECOGNITION

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:
http://ift.tt/2oYfnO4

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

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