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The reliable estimation of the pupil position is one the most important prerequisites in gaze-based HMI applications. Despite the rich landscape of image-based methods for pupil extraction, tracking the pupil in real-world images is highly challenging due to variations in the environment (e.g. changing illumination conditions, reflection, etc.), in the eye(More)
Post-chiasmal visual pathway lesions and glaucomatous optic neuropathy cause binocular visual field defects (VFDs) that may critically interfere with quality of life and driving licensure. The aims of this study were (i) to assess the on-road driving performance of patients suffering from binocular visual field loss using a dual-brake vehicle, and (ii) to(More)
Robust and accurate detection of the pupil position is a key building block for head-mounted eye tracking and prerequisite for applications on top, such as gaze-based human–computer interaction or attention analysis. Despite a large body of work, detecting the pupil in images recorded under real-world conditions is challenging given significant variability(More)
In many applications involving scanpath analysis, especially when dynamic scenes are viewed, consecutive fixations and saccades, have to be identified and extracted from raw eye-tracking data in an online fashion. Since probabilistic methods can adapt not only to the individual viewing behavior, but also to changes in the scene, they are best suited for(More)
Real-time, accurate, and robust pupil detection is an essential prerequisite for pervasive video-based eye-tracking. However, automated pupil detection in real-world scenarios has proven to be an intricate challenge due to fast illumination changes, pupil occlusion, non centered and off-axis eye recording, and physiological eye characteristics. In this(More)
Eyelid identification and aperture estimation provide key data that can be used to infer valuable information about a subject's mental state (e.g., vigilance, fatigue, and drowsiness) as well as validate or reduce the search space of other eye features. In this paper, we consider these tasks from the perspective of pervasive eye tracking, taking into(More)
The task of automatically tracking the visual attention in dynamic visual scenes is highly challenging. To approach it, we propose a Bayesian online learning algorithm. As the visual scene changes and new objects appear, based on a mixture model, the algorithm can identify and tell visual saccades (transitions) from visual fixation clusters (regions of(More)
Exploring the effects of expertise on eye movements and visual search behavior of surgeons may help to improve and speed up the training of novices. However, comparing scan patterns to each other is a non-trivial task. This work employs several state-of-the-art, automated scan pattern comparison methods to re-analyze eye-tracking data of neurosurgeons that(More)
Neuron morphology is frequently used to classify cell-types in the mammalian cortex. Apart from the shape of the soma and the axonal projections, morphological classification is largely defined by the dendrites of a neuron and their subcellular compartments, referred to as dendritic spines. The dimensions of a neuron’s dendritic compartment, including its(More)
The analysis of visual scanpaths, i.e., series of fixations and saccades, in complex dynamic scenarios is highly challenging and usually performed manually. We propose <b><i>SubsMatch</i></b>, a scanpath comparison algorithm for dynamic, interactive scenarios based on the frequency of repeated gaze patterns. Instead of measuring the gaze duration towards a(More)