VIIth Int. Workshop on Representation, analysis and recognition of shape and motion FroM Imaging data Call for Papers
FIRST CALL FOR PAPERS (Submission deadline: October 8, 2017)
VIIth Int. Workshop on Representation, analysis and recognition of
shape and motion FroM Imaging data
Centre Paul-Langevin Aussois - Savoie, France, 17-20 December, 2017.
http://www.arts-pi.org.tn/rfmi2017/index.html
Contact: Naoufel.Werghi@kustar.ac.ae
The rapid development of emerging imaging sensors technologies (3D/4D
cameras, medical imaging devices, cost-effective depth cameras, 3D/4D
microscopy, etc.) brings at forefront large imaging data in 2D, 3D and
4D and is pushing forth a new research direction to study patterns and
shapes from image data as well as their motion for advanced modeling,
statistical analysis and behavioral understanding.
The goal of the workshop is to promote interaction and collaboration
among researchers working on computer vision, machine learning and
computational geometry for the static and dynamic pattern recognition
and shape analysis as well as various applications, e.g., video scene
understanding, affective computing, human-machine interaction, computer
animation, robotics, cultural heritage conservation, healthcare assessment
and medical diagnostics. The perspective of RFMI will be to strengthen
the relationship between the many areas that have as a key meeting point,
the study of patterns and shapes and their motion from image data and the
design of relevant geometric and computational tools. Thus, it will be a
great opportunity to encourage links between researchers who share common
problems and frequently use similar tools.
The seventh edition of the international workshop on Representations,
analysis and recognition of shape and motion FroM Image data (RFMI 2017)
will take place at the Centre Paul-Langevin Aussois - Savoie, France.
It consists of three days oral sessions, poster sessions and outstanding
plenary invited talks. The workshop topics will feature not only sessions
on fundamental issues in computer vision, machine learning and computational
geometry but also specific tracks on various applications, e.g., Biometrics,
Surveillance and Analysis of humans, Biomedical Image Analysis and
Applications, and Art, Cultural Heritage and Entertainment.
It is planned to publish the RFMI 2017 proceedings by Springer in the
Communications in Computer and Information Science
series (http://www.springer.com/series/7899)
http://www.springer.com/us/book/9783319606538):
The endorsement of the workshop by the IAPR association is under process
(read about the previous edition in the IAPR newsletter
http://www.iapr.org/docs/newsletter-2017-02.pdf, pp. 25).
PAPER SUBMISSION AND REVIEW PROCESS
Submitted papers should describe substantial novel research achievements
about one of the related topics of the workshop or closely. Authors should
apply Springer conference paper templates, which can be find in the
author's instruction page here:
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0.
All submissions should be in Adobe Acrobat according to the latex templates.
The RFMI 2017 secretariat must receive your paper before October 8th, 2017, 10:00 PM GMT.
Papers with up to 15 pages and no less than 10 pages will be considered.
Submission implies the willingness of at least one of the authors to
register and to present the communication at the workshop, if accepted.
All papers submitted will be subjected to a blind review process by at
least three members of the program committee. The initial paper must not
provide names and affiliation, and should include a title, a 150-word
abstract, keywords and paper manuscript. Please submit your paper
electronically at our website using the CMT platform (the link will be
provided soon).
IMPORTANT DATES
Paper submission deadline October 8, 2017
Notification of acceptance November 19, 2017
Camera-ready November 31, 2017
Workshop December 17-20, 2017
INVITED SPEAKERS (preliminary list)
* Dr. David Gu http://www3.cs.stonybrook.edu/~gu/
Professor, State University of New York at Stony Brook (USA),
Title - Optimal Mass Transportation, Geometry and Deep Learning.
* Dr. Emanuele Rodolà https://sites.google.com/site/erodola/
Assistant Professor, Sapienza University of Rome (Italy)
Title - Geometric Deep Learning.
Contact: Naoufel.Werghi@kustar.ac.ae
Dr. Naoufel Werghi
Associate Professor
Electrical and Computer Engineering Department
PO Box 127788, Abu Dhabi, UAE
T +971 (0)2 501 8368
F +971 (0)2 447 2442
Naoufel.Werghi@kustar.ac.ae