Integration of goal-driven, top-down attention and image-driven, bottom-up attention is
crucial for visual search. Yet, previous research has mostly focused on models that are …

In natural vision both stimulus features and task-demands affect an observer's attention.
However, the relationship between sensory-driven (†œbottom-upâ€) and task-dependent …

Many experiments have shown that human behavior is nearly Bayes optimal in a variety of
tasks. This implies that neural activity is capable of representing both the value and …

Future interactive virtual environments will be “attention-aware,” capable of predicting,
reacting to, and ultimately influencing the visual attention of their human operators. Before …

Several advanced driver assistance systems realizing elementary perception and analysis
tasks have been introduced to market in recent years. For example, collision mitigation …

Weighted salience models are a popular framework for image-driven visual attentional
processes. These models operate by: sampling the visual environment; calculating feature …

People perform a remarkable range of tasks that require search of the visual environment for
a target item among distractors. The Guided Search model (Wolfe, 1994, 2007), or GS, is …

Artificial visual attention is one of the key methodologies inspired from nature that can lead
to robust and efficient visual search by machine vision systems. A novel approach is …

Even the enormous processing capacity of the human brain is not enough to handle all the
visual sensory information that falls upon the retina. Still human beings can efficiently …

Research on computer vision systems for driver assistance resulted in a variety of
approaches mainly performing reactive tasks like, eg, lane keeping. However, for a full …