Doctoral Project: Computational models of task dependent object-based visual attention
Part of research project: Object-level scene descriptions and attention in visual search
Description of the doctoral project
In this project we will explore the hypothesis that object-level attentional units are essential mid-level factors which guide human eye-movements in visual scene analysis. Based on eye-fixation data from visual search tasks we will first build computational models to emulate the measured fixation sequences, to quantify the influence of different low- and high-level visual features, and to characterize the influence of task-driven changes in object-based attention processes. In a second step, plausible models will be integrated as “attentional modules” into a computer vision system for visual scene analysis and will be evaluated in terms of task success and the number of computations involved. Potential achievement of the project is an efficient real-time analysis of dynamic visual scenes.
Project start date: October 1, 2019
Applicants must hold a Master degree in Computational Neuroscience, Computer Science, Physics, Mathematics, or related fields. Applicants should have very good programming skills, a solid mathematical background, competence in machine learning, and a strong interest in visual perception.