Research Themes

Scientific context

Computer-generated pictures and videos are now ubiquitous: both for leisure activities, such as special effects in motion pictures, feature movies and video games, or for more serious activities, such as visualization and simulation.

MAVERICK deals with image synthesis methods. We place ourselves at the end of the image production pipeline, when the pictures are generated and displayed. We take many possible inputs: datasets, video flows, pictures and photographs, (animated) geometry from a virtual world. We produce as output pictures to be displayed on screen as well as videos.

These pictures will be viewed by humans, and we consider this fact as an important point of our research strategy, as it provides the benchmarks for evaluating our results: the pictures and animations produced must be able to convey the message to the viewer. The actual message depends on the specific application: data visualization, exploring virtual worlds, designing paintings and drawings. Our vision is that all these applications share common research problems: ensuring that the important features are perceived, avoiding clutter or aliasing, efficient internal data representation, etc.

Computer Graphics, and especially MAVERICK is at the crossroad between fundamental research and industrial applications. We are both looking at the constraints and needs of applicative users and targeting long term research issues such as sampling and filtering.

Research axes

The MAVERICK project-team aims at producing representations and algorithms for efficient, high-quality computer generation of pictures and animations through the study of three connected axes:

measuring the impact of pictures, by developing perceptual error metrics, measuring and removing artefacts and discontinuities, evaluating the user response to pictures and algorithms,
developing representations for data, through abstraction, stylization and simplification,
developing new methods for predicting the properties of a picture (e.g. frequency content, variations) and adapting our image-generation algorithm to these properties.

Domains of application

We envision that these research topics will be applied to several domains, such as:

Computer Visualization, where we take as input a large localized dataset and represent it in a way that will let an observer understand its key properties,
Expressive Rendering, where we create an artistic representation of a virtual world,
Illumination Simulation, where our focus is modelling the interaction of light with the objects in the scene.
Complex Scenes, where our focus is generating, managing, animating and rendering highly complex scenes.

The heart of MAVERICK is therefore understanding what makes a picture useful, powerful and interesting for the user, and designing algorithms to create these pictures.

A fundamental element of the MAVERICK project-team is that the research axes and the application domains are all cross-connected. For example, our research on the impact of pictures can be applied to Computer Visualization, Expressive rendering and Illumination Simulation. Similarly, Illumination simulation as an application domain will draw from our research on all axes: impact, representations and prediction.

Transverse research issues

Besides the connections between our three research axes, we are interested in several fundamental problems which are transverse issues for all our applications:

sampling:: is an ubiquitous process occurring in all our application domains, whether photorealistic rendering (e.g. photon mapping), expressive rendering (e.g. brush strokes), texturing, fluid simulation (Lagrangian methods), etc. An important issue in for our research is ensuring the conflicting requirements of space-time coherence and homogeneity in object space and screen space at the same time.
filtering:: is another ubiquitous process, occuring in all our application domains, whether in realistic rendering (e.g. for integrating height fields, normals, material properties), expressive rendering (e.g. for simplifying strokes), textures (through non-linearity and discontinuities). performance and scalability: are also a common requirement for all our applications. We want our algorithms to be usable, which implies that they can be used on large and complex scenes, which places a great importance on scalability. We target interactive and real-time applications, with an update frequency between 10 Hz and 100 Hz.
phenomenological approach:: at the lowest level, the phenomena we are trying to model can be represented using atoms or photons and their interactions. However, this low-level representation is neither practical nor efficient. We are interested in extracting higher-level rules, whether for physical animation of fluids, for the properties of paints and strokes or for the frequency content of illumination.
textures:: (that is, mapped fields of attributes) are used more and more in various efficient representations, in realistic rendering (such as irradiance maps), in expressive rendering (for example advected patterns), in data visualization (for the colormap) in addition to the initial texturing field (which now extends to very high-resolution and non-color representation of details).
coherence and continuity:: in space and time is also a common requirement of realistic as well as expressive models which must be ensured despite contradictory requirements. We want to avoid flickering and aliasing.
animation:: our input data is likely to be time-varying (e.g. animated geometry, physical simulation, time-dependent dataset). A common requirement for all our algorithms is that they must be compatible with animated data (fast updates for data structures, low latency algorithms.).