Gilab’s research lines are: Videogames, Global illumination, Medical imaging, Scientific visualization, Viewpoint selection and Shape recognition, Computational aesthetics, e-learning and Spatial and spatio-temporal data processing. Gilab responds to the demand of the industrial sector in different areas such as computer games and medicine.
Our research is focused on algorithms for the illumination of virtual environments. We aim at reaching equilibrium between realism and computational cost, considering the purpose of the generated images. Thus, while applications to interior design and animation require a high realism, videogames would rather need real-time computations. Techniques as light-paths reuse allow improving the performance of classic global illumination algorithms, based on ray-tracing and radiosity. In the case of videogames, techniques involving GPU, simplification of algorithms, and non-physically-realistic rendering, are used in order to approach real time computations.
During last years the fast increasing power of Graphics Processing Units (GPU’s) have supplied videogames with the posibility of enormously increasing graphics realism. Our research is centered on the application of existing graphics technics, or when necessary on the creation of new ones, to videogames. This needs the integration of the techniques, once adapted or simplified to run in real-time, in the “game engine”, the software system that runs the game. Nowadays, game engines are not only used to make games but they are the basic tool in virtual reality systems, simulation, and virtual settings for movies and broadcasting.
The Legends of Girona and the Jaume I videogames can be seen here.
GIlab works in collaboration with medical staff from the Institut de Diagnòstic per la Imatge, a prestigious imaging institute located in the main Catalan public hospitals, and with doctors from the Hospital Clínic de Barcelona. The goal of this multidisciplinary team is to research and develop useful solutions for the technical and clinical problems in the field of medical imaging and develop new tools to support diagnosis. Our research covers: basic tools for diagnosis, computer aided diagnosis, and diffusion tensor imaging.
Scientific visualization describes the field of computer science which deals with the study and definition of algorithms and data structures for the visualization of scientific data. Visualization has become one of the most important ways of exploring data and it is applied in many scientific fields and application areas, such as material sciences, fluid dynamics, environmental sciences or medicine. In our group we investigate visualization and simplification techniques for exploring 3D medical data.
Viewpoint Selection and Shape Recognition
Viewpoint selection is an emerging area in computer graphics with applications in fields such as scene exploration, image-based modelling, and volume visualization. We investigate viewpoint quality measures to select the best views and to explore a scene. We also study the information and saliency associated with the different parts of an object. Some of those measures are used to simulate the illumination of a scene. In the object recognition field, we are working in the definiton of shape descriptors based on uniform distributions of lines and viewpoint techniques. These descriptors permit us to calculate the similarity between objects of large databases.
Computational aesthetics joins together different fields such as computer science, philosophy, psychology, and the arts. In particular, we investigate informational aesthetic measures to quantify order, complexity and information in images, paintings, and sculptures. The used techniques are mainly based on information theory, Kolmogorov complexity, and viewpoint selection quality measures.
E-learning is a very extensive research field. Our group focuses on the development of specialized web based tools for the automatic correction of complex open-answer activities. Within this context, we develop correctors for math, programming, database design, diagrams or graphs exercises. These correctors are integrated into the ACME e-learning platform. Currently, this platform has more than 4.000 users and is applied in more than 40 different subjects. Our investigation is also focused on automatic assessment.
Spatial and Spatio-Temporal Data Processing
Research in this area is focused on spatial and spatio-temporal data mining with the aim of facilitating decision making in fields such as facility location, competitive-collaborative marketing, vehicle traffic management, urban planning, touristic development, medicine, epidemiology, and the study of social interactions. We develop algorithms and data structures to extract meaningful non-explicit information from the spatial databases. As experts in the area of Computational Geometry and the use of the GPU, and facing the challenge of the Big Data, we seek efficient solutions which usually are, totally or partially, obtained in parallel.