Thesis and HDR defended in 2009
PhD Thesis: Adrien Bousseau
Visual communication greatly benefits from the large variety of appearances that an image can take. By neglecting spurious details, simplified images focus the attention of an observer on the essential message to transmit. Stylized images, that depart from reality, can suggest subjective or imaginary information. More subtle variations, such as change of lighting in a photograph can also have a dramatic effect on the interpretation of the transmitted message.
The goal of this thesis is to allow users to manipulate visual content and create images that corresponds to their communication intent. We propose a number of manipulations that modify, simplify or stylize images in order to improve their expressive power.
We first present two methods to remove details in photographs and videos. The resulting simplification enhances the relevant structures of an image. We then introduce a novel vector primitive, called Diffusion Curves, that facilitates the creation of smooth color gradients and blur in vector graphics. The images created with diffusion curves contain complex image features that are hard to obtain with existing vector primitives. In the second part of this manuscript we propose two algorithms for the creation of stylized animations from 3D scenes and videos. The two methods produce animations with the 2D appearance of traditional media such as watercolor. Finally, we describe an approach to decompose the illumination and reflectance components of a photograph. We make this ill-posed problem tractable by propagating sparse user indications. This decomposition allows users to modify lighting or material in the depicted scene.
The various image manipulations proposed in this dissertation  facilitates the creation of a variety of visual representations, as illustrated by our results.
PhD Thesis: Alexandrina Orzan
This thesis  proposes a novel image primitive - the diffusion curve. This primitive relies on the principle that images can be defined via their discontinuities, and concentrates image features along contours. The diffusion curve can be defined in vector graphics, as well as in raster graphics, to increase user control during the process of art creation. The vectorial diffusion curve primitive augments the expressive powers of vector images by capturing complex spatial appearance behaviors. Diffusion curves represent a simple and easy-to-manipulate support for complex content representation and edition. In raster images, diffusion curves define a higher level structural organization of the pixel image. This structure is used to create simplified or exaggerated representations of photographs in a way consistent with the original image content. Finally, a fully automatic vectorization method is presented, that converts raster diffusion curve to vector diffusion curve.
PhD Thesis: Lionel Baboud
This thesis deals with real time image synthesis, and especially efficient rendering of visual detail, which is a source of realism in synthetic images. To face the complexity of visual detail, one needs specific representations adapted to both the represented data (e.g. geometry, materials) and the hardware capabilities. The first contribution of this thesis is a technique for representing geometric detail using relief textures. Two algorithms have been derived to render such height field data on the GPU: the first one accepts dynamic input while the second one produces even improved results on static scenes, at the expense of some pre-computation. These techniques are also extended to represent water and light interaction in water in real time. A second contribution of this thesis is to derive adapted representations of far away objects, to allow rendering the appearance of an object without dealing with complex geometry, from the lightfield data of this object. This is for instance applied to models of trees. The thesis was defended on November 12, 2009.