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BIOVISION Research team

Biologically plausible Integrative mOdels of the Visual system : towards synergIstic Solutions for visually-Impaired people and artificial visiON

  • Leader : Bruno Cessac
  • Type : team
  • Research center(s) : Sophia
  • Field : Digital Health, Biology and Earth
  • Theme : Computational Neuroscience and Medicine
  • Inria teams are typically groups of researchers working on the definition of a common project, and objectives, with the goal to arrive at the creation of a project-team. Such project-teams may include other partners (universities or research institutions)

Team presentation

Vision is a key function to sense the world and perform complex tasks, with a high sensitivity and a strong reliability, given the fact that most of its input is noisy, changing and ambiguous. Better understanding biological vision will have a strong scientific, medical, societal and technological impact in the near future. In this context, Biovision aims at developing fundamental research as well as technological transfer along two axes:


Axis 1 focuses on the development of high tech vision aid systems for low vision patients.
Axis 2 focuses on the precise modeling of the visual system for normal and distrophic conditions,
targeting applications for low vision and blind patients.

These axes are developed in strong synergy, involving a large network of national and international collaborators
with neuroscientists, physicians, and modellers.

Research themes

Axis 1: High tech vision aid systems for low vision patients
The most popular class of vision aid systems for low vision patients is based on the idea of magnification.
These aids are helpful for tasks such as reading but of course are not useful in other common daily tasks such
as navigation. Video goggles are another kind of device where visual information is captured by a head-mounted camera,
processed and then displayed on a near-the-eye display screen. So far, this technology did not encountered a
big success essentially due to their narrow field of view. This situation could evolve with the fast progression
of technology around virtual reality and augmented reality.
In BIOVISION we mainly focus on this technology to develop new vision aid systems that could take into
account the pathologies of low vision patients but also on the tasks performed by the patients. We have three
main goals:


1. We plan to focus on three tasks: reading, watching movies and navigating (indoor or outdoor), which
are all important daily life activities for patients.
2. We aim at proposing new scene enhancements depending on pathologies.
3. We want to test them in immersive environments with low vision patients, taking into consideration
ergonomics.

 


Axis 2: Human vision understanding through joint experimental and modeling studies, for normal and distrophic retinas

A holistic point of view is emerging in neuroscience where one can observe simultaneously how vision works
at different levels of the hierarchy in the visual system. Multiple scales functional analysis and connectomics
are also exploding in brain science, and studies of visual systems are upfront on this fast move. These integrated
studies call for new classes of theoretical and integrated models where the goal is the modeling of visual
functions such as motion integration.
In BIOVISION we contribute to a better understanding of the visual system with three main goals:


1. We aim at proposing simplified mathematical models characterizing how the retina converts a visual
scene into spike population coding, in normal and under specific pathological conditions.
2. We want to design an integrated numerical model of the visual stream, with a focus on motion
integration, from retina to visual cortex area (e.g., the motion stream V1-MT-MST).
3. We plan to develop a simulation platform emulating the retinal spike-response to visual and
prosthetic simulations, in normal and pathological conditions.

 

Finally, although this is not the main goal of our team, another natural avenue of our research will be to develop
novel synergistic solutions to solve computer vision tasks based on bio-inspired mechanisms.

International and industrial relations

  • Institut de Neurosciences de la Timone, Marseille, France
  • Institut de la Vision, Paris, France .
  • Laboratoire de Psychologie Cognitive, Aix-Marseille Université, France
  • Institute for Adaptive and Neural Computation, University of Edinburghn Edinburgh, United Kingdom
  • Department of Informatics, Bioengineering, Robotics, and Systems
    Engineering-DIBRIS, University of Genova, Genova, Italy
  • Universidad de Guanajuato, Departamento de Ingeniería Electrónica, Mexico
  • Institute of Neuroscience, Newcastle University, Newcastle, United Kingdom
  • Institute of Neural Information Processing, Faculty of Engineering and Computer
    Sciences, Ulm University, Ulm, Germany
  • UVal Centro Interdisciplinario de Neurociencia de Valparaiso, Valparaiso University,
    Valparaiso, Chili

Keywords: Visual neuroscience Low-vision Retina therapy Bio-inspired vision Computer vision Modelling