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IP4EC

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Image processing for enhanced cinematography

The objective is to develop image processing algorithms for cinema that allow people watching a movie on a screen to see the same details and colors as people at the shooting location can. It is due to camera and display limitatio... ver más

31/03/2018

UPF

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

UNIVERSITAT POMPEU FABRA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 322

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2018-03-31 No tenemos la información de la convocatoria

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Información adicional privada

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1 Participantes

UPF

0.00€ | Lider

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Líder del proyecto

UNIVERSITAT POMPEU FABRA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 322

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The objective is to develop image processing algorithms for cinema that allow people watching a movie on a screen to see the same details and colors as people at the shooting location can. It is due to camera and display limitations that the shooting location and the images on the screen are perceived very differently. We want to be able to use common cameras and displays (as opposed to highly expensive hardware systems) and work solely on processing the video so that our perception of the scene and of the images on the screen match, without having to add artifical lights when shooting or to manually correct the colors to adapt to a particular display device. Given that in terms of sensing capabilities cameras are in most regards better than human photoreceptors, the superiority of human vision over camera systems lies in the better processing which is carried out in the retina and visual cortex. Therefore, rather than working on the hardware, improving lenses and sensors, we will instead use, whenever possible, existing knowledge on visual neuroscience and models on visual perception to develop software methods mimicking neural processes in the human visual system, and apply these methods to images captured with a regular camera. From a technological standpoint, reaching our goal will be a remarkable achievement which will impact how movies are made (in less time, with less equipment, with smaller crews, with more artistic freedom) but also which movies are made (since good-visual-quality productions will become more affordable.) We also anticipate a considerable technological impact in the realm of consumer video. From a scientific standpoint, this will imply finding solutions for several challenging open problems in image processing and computer vision, but it also has a strong potential to bring methodological advances to other domains like experimental psychology and visual neuroscience.

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