PhD Scholarship for research in visual quality metrics
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At the Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain, there is a PhD scholarship available for research on visual quality metrics. This position is associated with the ERC Starting Grant "Image processing for enhanced cinematography”, led by Marcelo Bertalmío, http://www.dtic.upf.edu/~mbertalmio/, and which is described below.
This work would be done under Dr. marcelo bertalmío supervision, over a 4-year period, and the PhD thesis should be completed within this timeframe. The scholarship covers tuition fees, does not require teaching, and the monthly wage is 1,300€. The admission requirements are: to have completed 300 ECTS credits, 60 of which have to correspond to an official, research-oriented Master's program.
Scholarships and admission are very competitive, and a strong background in math, image processing, computer vision, neuroscience or related disciplines are a plus.
Contact: please send application with CV, contact information of three references, and an intention letter to: marcelo DOT bertalmio AT upf DOT edu . We will start evaluating applications in early July and the position will be open until filled.
Universitat Pompeu Fabra (UPF, http://www.upf.edu/en/) is a public university located in Barcelona. It is the best Spanish university according to the London Times higher education index, 2011, and it's the number one Spanish university in number of ERC grants. The Information and Communication Technology department (ICT, http://www.upf.edu/dtic/en/) is the best in Computer Science in Spain, according to the Shanghai index 2009.
Description of the project
The objective of this ERC Starting Grant project 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 artificial lights when shooting (other than for artistic purposes) or to manually correct the colors to adapt to a particular display device. In terms of sensing capabilities cameras are in many regards better than human photoreceptors, but human vision performs better processing, 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. We will also use variational methods coupled with perceptual metrics to optimize the final outputs. 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.