Decoding visual cognition from non-invasive measurements of brain activity has shown valuable applications. Vision-based Brain-Computer Interfaces (BCI) systems extend from spellers to database search and spatial navigation. Despite the high performance of ...
Stereo reconstruction is a problem of recovering a 3d structure of a scene from a pair of images of the scene, acquired from different viewpoints. It has been investigated for decades and many successful methods were developed.The main drawback of these ...
The application of Bayesian modeling techniques is increasingly common in neuroscience due to the coherent and principled way in which the paradigm deals with uncertainty. The Bayesian framework is particularly valuable in the context of complex, ill-posed ...
Artists often take advantage of the limitations of the human visual system to create art that provides new experiences for the observers. Similarly, in this thesis, we explore new computational artistic compositions that create new visual experiences by re ...
Traditionally, human vision research has focused on specific paradigms and proposed models to explain very specific properties of visual perception. However, the complexity and scope of modern psychophysical paradigms undermine the success of this approach ...
In crowding, perception of an object deteriorates in the presence of nearby elements. Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation, to date there exists no consensus on how to model it. Previous experiments show ...
Flying robots are increasingly used for tasks such as aerial mapping, fast exploration, video footage and monitoring of buildings.
Autonomous flight at low altitude in cluttered and unknown environments is an active research topic because it poses challen ...
