[visionlist] [Call for participants]: Group evaluation of sclera segmentation models

[Vitomir Štruc]

CALL FOR PARTICIPANTS:  GROUP EVALUATION OF SCLERA SEGMENTATION MODELS


*** INTRODUCTION ***

Sclera biometrics have gained significant popularity among emerging 
ocular traits in the last few years. In order to establish the sclera as 
a viable biometric trait and to evaluate its potential for automated 
biometric systems, several works have been presented in the literature, 
employing sclera both individually and in combination with the iris. 
Despite these initiatives, sclera biometrics need to be studied more 
extensively to ascertain their usefulness. Among the numerous challenges 
still open in this area, efficient and robust sclera segmentation is 
among the most important ones, affecting all downstream tasks from 
normalization to recognition. While a considerable amount of research 
has been directed towards sclera segmentation in recent years, the 
performance of existing techniques especially in various scenarios are 
still not well explored.

Several group benchmarking efforts have been organized in the scope of 
major biometric conferences to address this gap, namely SSBC 2015, SSRBC 
2016, SSBC 2016, SSERBC 2017, SSBC 2018 and SSBC 2019 that were held in 
conjunction with BTAS 2015, ICB 2016, BTAS 2016, IJCB 2017, ICB 2018 and 
ICB 2019, respectively. The latest in the series, SSBC 2020m was 
organized in the scope of IJCB 2020 and explored the performance of 
sclera segmentation models in mobile settings.

As the next step in the series of competition, the organizers of SSBC 
2020 are planning to conduct the largest group benchmarking effort to 
date and submit the results and corresponding analysis to a *** major 
biometric journal (TBD) ***. The paper describing the group benchmarking 
effort will be ***co-authored by all participants ***.

The planned paper will be partially based on the submissions to SSBC 
2020 but will include new experiments on multiple datasets that will 
allow for a more detailed analysis of the results with novel insights. 
We invite researchers working on problems related ocular biometrics and 
sclera segmentation to take part in the benchmarking effort and 
contribute models for scoring and analysis. The benchmarking effort is 
open to anyone and is not limited solely to participants of previous 
benchmarking competitions.

Webpage: https://sites.google.com/view/ssbc2020/group-evaluation



*** BENCHMARKING LOGISTICS ***

Participants will be given training datasets to develop and train their 
segmentation models. A list of experiments will be provided and 
instructions on how to train multiple instances of the developed model. 
All trained models will then have to be tested on a number of test 
datasets. The organizers will score and analyze the submitted results.


*** REGISTRATION PROCEDURE ****

Researchers interested in participating should send an e-amil to Dr. 
Abhijit Das with the subject line "Post SSBC 2020 benchmarking effort" 
with the following information: Name, Affiliation, Email, Phone number, 
CV, Mailing Address.

*** TIMELINE ***

Registration starts 8th September 2020

Training datasets available 8th September 2020

Test dataset made available 8th September2020

Registration closes 10th October 2020

Result submission deadline 10th October 2020



**** ORGANIZERS ***

Dr. Abhijit Das,Indian Statistical Institute, Kolkata, India 
(abhijit.das at inria.fr)

Prof. Umapada Pal, Indian Statistical Institute, Kolkata, India

Matej Vitek, PhD candidate, University of Ljubljana, Ljubljana, Slovenia

Prof. Peter Peer, University of Ljubljana, Ljubljana, Slovenia

Assoc. Prof. Vitomir Štruc, University of Ljubljana, Ljubljana, Slovenia

-- 
Assoc. Prof. Vitomir Struc, PhD
Laboratory for Machine Intelligence
Faculty of Electrical Engineering
University of Ljubljana
Slovenia
Tel: +386 1 4768 839
Fax: +386 1 4768 316
URL: https://lmi.fe.uni-lj.si/en/vitomir-struc/

Program Co-Chair: International Joint Conference on Biometrics (IJCB 2020)
Workshop Co-Chair: Winter Conference on Applications in Computer Vision (WACV 2021)