2016-10-26 : EUVIP Special Session on Biologically Inspired Computer Vision

description of the session

Recent advances in imaging technologies have yielded scientific data at unprecedented detail and volume, leading to the need of a shift of paradigm in image processing and computer vision. Beyond the usual classical von Neumann architecture, one strategy that is emerging in order to process and interpret this amount of data follows from the architecture of biological organisms and shows for instance computational paradigms implementing asynchronous communication with a high degree of local connectivity in sensors or brain tissues. This session aims at bringing together researchers from different fields of Biologically Inspired Computer Vision to present latest results in the field, from fundamental to more specialized topics, including visual analysis based on a computational level, hardware implementation, and the design of new more advanced vision sensors. It is expected to provide a comprehensive overview in the computer area of biologically motivated vision. On the one hand, biological organisms can provide a source of inspiration for new computationally efficient and robust vision models and on the other hand machine vision approaches can provide new insights for understanding biological visual systems. This session covers a wide range of topics from fundamental to more specialized topics, including visual analysis based on a computational level, hardware implementation, and the design of new more advanced vision sensors. In particular, we expect to provide an overview of a few representative applications and current state of the art of the research in this area.

• URL http://www-l2ti.univ-paris13.fr/euvip2016/index.php/86-euvip2016/129-tentative-technical-program-in-detail

• date October 26th, 2016

• Location Ecole Centrale Marseille

• Address 38 rue Frederic Joliot-Curie 13013 Marseille, France Phone : +33 (0)4 91 05 45 45

• Programme

• 13.50 Visual System Inspired Algorithm For Contours, Corner And T Junction Detection, Antoni Buades, Rafael Grompone Von Gioi

• 13.50 Biologically-inspired characterization of sparseness in natural images, Laurent Perrinet

• 14.10 Color filter array imitating the random nature of color arrangement in the human cone mosaic, Prakhar Amba, David Alleysson

• 14.30 An Illuminant-Independent Analysis Of Reflectance As Sensed By Humans, And Its Applicability To Computer Vision, Alban Flachot, Phelma, J.Kevin O’Regan, Edoardo Provenzi

• 14.50 Categorization of microscopy images using a biologically inspired edge co-occurrences descriptor, Lionel Fillatre, Michel Barlaud, Laurent Perrinet