Objective
Virtual reality systems offer exciting possibilities. We propose to help construct virtual reality databases automatically from sequences of images taken by moving camera(s). Such sequences contain, a priori, the necessary information for being able to determine the 3D structure of a scene and its photometric aspects.
APPROACH AND METHODS
The principal objective is to define and develop algorithms for extracting data from sequences of images acquired with a slowly moving camera. We hope to define a sequence of operations such that the construction of the database from the sequences of images is as automatic as possible.
- Existing computer vision research shows that it is possible to extract the 3D structure of a scene which is observed by a stereovision setup or by a camera following an unknown path.
However, the 3D structure and the motion are note very precisely estimated and the consortium will explore new ideas to improve these results. It will also address the internal parameters of the camera changing during a sequence (zoom for example).
- To compute a realistic view of a scene, we must not only know the structure of the scene but also we must determine how the surfaces reflect light. The BRDF (Bidirectional Reflection Distribution Function) completely characterises surface properties at a given level of resolution. It is the most natural description of local surface properties. We will study how to estimate it from the sequences of images and from the estimated structure of the scene.
We will also work on 3D texture as a means to characterise the reflectance of materials at any scale.
- The information which could be obtained by analysing the sequences will probably be very different from the ones which are obtained usually by constructing databases from maps by an operator. We will explore how the data structures can be adapted to the requirements of virtual reality systems.
POTENTIAL
Our first result will be to provide new interesting insights in the three research areas that we address: structure from motion in computer vision, understanding of the reflectance properties of materials and synthesis of images from noisy and unstructured data. We aim to setup the following exciting demonstration: select an old film which includes sequences of images of a building which no longer exists and then create a database for it. Other possibilities include the construction of databases necessary for the simulation of driving cars, trains, boats, planes or for the design of furniture.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences databases
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors optical sensors
- natural sciences computer and information sciences artificial intelligence computer vision
- natural sciences computer and information sciences software software applications virtual reality
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Programme(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Coordinator
91404 Orsay
France
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