Optimal Cue Combination for Saliency Computation: A Comparison with Human Vision
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Objective. Artificial vision has been and still is the subject of intense research. The ultimate goal is to help blind people in their daily life. Approaches to artificial vision, including visual prostheses and optogenetics, have strongly focused on resto ...
More and more intelligent systems have to interact with humans. In order to communicate efficiently, these systems need to perceive and understand us. A key factor of communication is the people's visual focus of attention (VFOA), which is useful to estima ...
Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...
In the classic model of vision, processing is local, feedforward and hierarchical. The first stages of the visual system are retinotopic, i.e., neighboring points in the outside world are mapped onto neighboring photoreceptors of the retina and this is pre ...
In previous research, microsaccades have been suggested as psychophysiological indicators of task load. So far, it is still under debate how different types of task demands are influencing microsaccade rate. This piece of research examines the relation bet ...
Classically, vision is seen as a cascade of local, feedforward computations. This framework has been tremendously successful, inspiring a wide range of ground-breaking findings in neuroscience and computer vision. Recently, feedforward Convolutional Neural ...
Human vision has evolved to make sense of a world in which elements almost never appear in isolation. Surprisingly, the recognition of an element in a visual scene is strongly limited by the presence of other nearby elements, a phenomenon known as visual c ...
The interaction with the various learners in a Massive Open Online Course (MOOC) is often complex. Contemporary MOOC learning analytics relate with click-streams, keystrokes and other user-input variables. Such variables however, do not always capture user ...
Modelling human visual attention is of great importance in the field of computer vision and has been widely explored for 3D imaging. Yet, in the absence of ground truth data, it is unclear whether such predictions are in alignment with the actual human vie ...
In serial dependence (SD), features of a present stimulus are judged as similar to previously presented ones. This bias is often explained by a continuity field (CF) in perception, combining similar stimuli in an extended region of space (∼ 15°) and time ( ...
