EU Projects - Past

H2020 FET Renvision (Participant)

Project site:

The retina is a sophisticated distributed processing unit of the central nervous system encoding visual stimuli in a highly parallel, adaptive and computationally efficient way. Recent studies show that rather than being a simple spatiotemporal filter that encodes visual information, the retina performs sophisticated non-linear computations extracting specific spatio-temporal stimulus features in a highly selective manner (e.g. motion selectivity). Understanding the neurobiological principles beyond retinal functionality is essential to develop successful artificial computer vision architectures.

RENVISION's goal is, therefore, twofold:

  1. to achieve a comprehensive understanding of how the retina encodes visual information through the different cellular layers;
  2. to use such insights to develop a retina-inspired computational approach to high-level computer vision tasks.

To this aim, exploiting the recent advances in high-resolution light microscopy 3D imaging and high-density multielectrode array technologies, RENVISION will be in an unprecedented position to investigate pan-retinal signal processing at high spatio-temporal resolution, integrating these two technologies in a novel experimental setup. This will allow for simultaneous recording from the entire population of ganglion cells and functional imaging of inner retinal layers at near-cellular resolution, combined with 3D structural imaging of the whole inner retina. The combined analysis of these complex datasets will require the development of novel multimodal analysis methods.

Resting on these neuroscientific and computational grounds, RENVISION will generate new knowledge on retinal processing. It will provide advanced pattern recognition and machine learning technologies to ICTs by shedding a new light on how the output of retinal processing (natural or modelled) allows solving complex vision tasks such as automated scene categorization and human action recognition.

RENVISION Project overview


Project site:

SCENEUNDERLIGHT leverages the privileged role of Europe in photonics as well as in smart lighting technologies. We propose 1. training of early stage researchers, who would become future experts in computer vision and lighting technologies, 2. first-class research, to push the state-of-the-art of computer vision and to drive the changes of lighting technologies, and 3. new disruptive products in smart lighting to accelerate the technological transfer from academia to industry. The proposed program will make efforts on systems for energy saving, towards a more sustainable greener Europe. We plan to implement this directive by smart lighting, defining new disruptive light management system technologies. Our planned demonstrator will take long-term time-lapse top-view images of the environment, understanding it by means of computer vision algorithms and controlling lights, for optimal lighting and energy saving. This will proceed via estimating the scene illumination properties (3D structure, material of objects and light source positions) and its use, with respect to the activities of the people. Finally, all research results will converge into the creation of an “invisible light switch”: users moving within an environment (e.g. warehouse with multiple aisles) will have the feeling that all of it is lit (e.g. switching lights on in an aisle just before the person turns into it), while the system will actually manage lighting to save energy, switching off those which the user cannot see, as for an “energy saving in the invisible”.

Light modelling