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8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)

December 1–3, 2014 | Boston, Massachusetts, United States

CALL FOR PAPERS: Special Track on Bio-Inspired Machine Vision (BIMV)

Hosted at the 8th 8th International Conference on Bio-inspired Information and Communications Technologies (BICT 2014) - formerly BIONETICS

December 1 - 3, 2014
Boston, MA, USA

In-corporation with ACM SIGSIM

While machine vision systems are becoming increasingly powerful, in most regards they are still far inferior to their biological counterparts. For instance, in terms of object segmentation, recognition of object categories, viewpoint and lighting invariance, or material recognition, much can be learned from the visual systems of humans and animals. Studying the biological systems and applying the findings to the construction of computational vision models and artificial vision systems is therefore a promising way of advancing the field of machine vision. Conversely, evaluating the performance of such models and systems in comparison to the biological systems can provide important feedback for a better understanding of the brain mechanisms underlying natural vision. Bio-inspired machine vision is thus a truly interdisciplinary research endeavor that benefits all scientific disciplines involved.

The objective of the Special Track on Bio-Inspired Machine Vision is to bring together scientists from fields such as computer science, engineering, psychology, neuroscience, and biology to discuss their current work relating to this research effort. This track will provide an opportunity for exchanging research ideas and initiating cross-disciplinary research partnerships that will lead to novel approaches and developments in both machine vision and the study of biological vision. To achieve its objective, this special track seeks high-quality, original and unpublished papers addressing topics relevant to the issues raised above, for example:

  • Psychophysical, neuroimaging, EEG, or TMS studies of the human visual system that are relevant to computational vision models or machine vision applications
  • Studies of vision in animals with results that apply to computational models or technical applications in vision
  • Implementation and evaluation of biologically inspired components in machine vision systems
  • Systematic evaluation of biologically inspired artificial vision systems and comparison of the results to behavioral or neurophysiological data
  • Biologically motivated computational models of specific aspects of biological vision that are relevant to technical vision applications
  • Deep learning approaches to machine vision
  • Evaluation of human or animal vision with regard to ideal observer models
  • Studies of visual attention in humans or animals that may inform the implementation of attentional mechanisms in technical vision systems
  • Implementation and evaluation of mechanisms of location-, feature-, or object-based attention in artificial vision systems or computational models of vision


Authors are invited to submit regular papers (up to 8 pages each), short papers (up to 4 pages each) or poster/demo papers (up to 2 pages each) in ACM format. Up to two extra pages are allowed for each paper with extra page charges. See for more details.


All accepted paper will be published by ACM and submitted for indexing by SI, EI Compendex, Scopus, ACM Library, Google Scholar and many more. Selected papers will be considered for publication in leading journals including:

Important Dates:

Regular paper submission due: September 1
Short and poster/demo paper submission due: September 22
Notification for regular papers: September 22
Notification for short and poster/demo papers: October 6
Camera ready due: October 13

Program Committee Members:

Erhardt Barth, University of Luebeck, Germany

Vincent Courboulay, Université de La Rochelle, France

David Fofi, University of Burgundy, France

Tyler Garaas, Mitsubishi Electric Research Labs, Cambridge, MA

Nurit Haspel, University of Massachusetts Boston, MA

Pierre Kornprobst, INRIA, Sophia-Antipolis, France

Martin Lages, University of Glasgow, Scotland

Gang Luo, Schepens Eye Research Institute, Boston, MA

Pabitra Mitra, Indian Institute of Technology, Kharagpur, India

Heiko Neumann, University of Ulm, Germany

Rajarshi Pal, Indian Institute of Technology, Kharagpur, India

Marc Pomplun, University of Massachusetts Boston, MA

Florian Raudies, Boston University, Boston, MA

Antonio Rodriguez-Sanchez, University of Innsbruck, Austria

Samuel Romero-Garcia, University of Granada, Spain

Silvio Sabatini, University of Genoa, Italy

AbdElrahman Shabayek, Suez Canal University, Egypt

Track Chairs:

Marc Pomplun, University of Massachusetts at Boston, Boston, MA

Tyler Garaas, Mitsubishi Electric Research Laboratories, Cambridge, MA

Florian Raudies, Boston University, Boston, MA