[Imageworld] Call for papers for IJCV special issue on Omnidirectional Vision and Camera Networks and Non-classical Cameras

[Rahul.Swaminathan at telekom.de]

International Journal of Computer Vision: 

Special Issue on Omnidirectional Vision, Camera Networks 

and Non-classical Cameras

 

The International Journal of Computer Vision (IJCV) is organizing a
Special Issue on Omnidirectional Vision, Camera Networks and
Non-classical Cameras. 

Research on omnidirectional vision, camera networks and non-classical
cameras was originated by the need to overcome the visibility
restrictions of classical cameras. Since its starting days, this
research field has experienced a stable scientific advancement leading
both to significant progress in the theoretical knowledge and to its
exploitation within various application domains, including but not
limited to video surveillance, mobile and service robotics and medical
imaging.

Today, omnidirectional vision, camera networks and non-classical cameras
remain very active research fields. For example, several geometrical
aspects related to structure from motion and 3D reconstruction are still
under investigation for several kinds of non-classical sensors; optical
aspects and algorithmic issues are currently studied in the design of
new sensors and efficient applications; non-standard techniques are
conceived to cope with the intrinsic complexity of camera network
systems.

High quality contributions are sought on original research results on
any aspect of omnidirectional vision, camera networks and non-classical
cameras, including novel sensor design, applications of panoramic
vision, and scalable algorithms for large-scale camera networks. The
sought contributions include extended and improved versions of papers
presented at the 2008 Workshop on Omnidirectional Vision, Camera
Networks, and Non-classical Cameras (OMNIVIS 2008) but also any other
high quality, unpublished research results on the themes of this special
issue.

 

Areas of interest include, but are not limited to:

*         Omnidirectional vision

o        structure-from-motion

o        central and noncentral cameras

o        visual servoing

o        image processing

o        applications

*         Non-classical sensors

o        algorithms and calibration

o        novel, application-tailored designs

*         Large- (>1000) and medium-scale (10-1000) camera networks

o        decentralized algorithms robust to node failures

o        continuous calibration, e.g., of non-stationary camera networks

o        camera deployment and distributed calibration applications:
surveillance, tele-immersion, intelligent environments

 

Submission should follow the IJCV guidelines and will be reviewed
accordingly.

Submission deadline

Papers are due by: April 2, 2009

Guest Editors

*         Rahul Swaminathan, Deutsche Telekom Research Labs, Germany

*         Vincenzo Caglioti, Politecnico di Milano, Italy

*         Antonis Argyros,University of Creete  Greece

*         Shree Nayar, Columbia University, USA 

*         Yasushi Yagi, Osaka University, Japan

Instructions for authors

In order  to submit your manuscript to the International Journal of
Computer Vision please click on the URL below and in the tool bar under
the journal name.Click on "register" and put in your relevant
information.. This will give you a username and password, via email, so
that you will be able to submit your manuscript through the electronic
site. When submitting to the special issue, please select the "article
type" and click on the special issue that is appropriate
(Omnidirectional Vision).
 
This system supports a wide range of submission file formats: 
for manuscripts - Word, WordPerfect, RTF, TXT and Latex;
for figures - TIFF, GIF, JPEG, EPS, PPT, and Postscript.
PDF & PS are not an acceptable file formats for manuscripts.
  
http://visi.edmgr.com
<https://webmail.elet.polimi.it/Redirect/visi.edmgr.com> 
 
Please do not hesitate to contact Betty Pinney at
betty.pinney at springer.com or omnivis2008 at ics.forth.gr in case of
problems. 

 

 

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