Related papers: A temporally quantized distribution of pupil diame…
In this paper we present a new approach for pupil segmentation. It can be computed and trained very efficiently, making it ideal for online use for high speed eye trackers as well as for energy saving pupil detection in mobile eye tracking.…
Assessing cognitive workload is crucial for human performance as it affects information processing, decision making, and task execution. Pupil size is a valuable indicator of cognitive workload, reflecting changes in attention and arousal…
Cognitive workload is a topic of increasing interest across various fields such as health, psychology, and defense applications. In this research, we focus on classifying cognitive workload using the COLET dataset, employing a window-based…
Cognitive load theory (CLT) provides us guiding principles in the design of learning materials. CLT differentiates three different kinds of cognitive load -- intrinsic, extraneous and germane load. Intrinsic load is related to the learning…
Measuring pupil diameter is vital for gaining insights into physiological and psychological states - traditionally captured by expensive, specialized equipment like Tobii eye-trackers and Pupillabs glasses. This paper presents a novel…
Recently, researchers started using cognitive load in various settings, e.g., educational psychology, cognitive load theory, or human-computer interaction. Cognitive load characterizes a tasks' demand on the limited information processing…
The relationship between brain lateralization and cognitive functions is well-documented. The left hemisphere primarily handles tasks such as language and arithmetic, while the right hemisphere is involved in creative activities like…
Neural network-based clustering has recently gained popularity, and in particular a constrained clustering formulation has been proposed to perform transfer learning and image category discovery using deep learning. The core idea is to…
It is well known that a systematic analysis of the pupil size variations, recorded by means of an eye-tracker, is a rich source of information about a subject's arousal and cognitive state. Current methods for pupil analysis are limited to…
Cognitive load assessment is crucial for understanding human performance in various domains. This study investigates the impact of different task conditions and time constraints on cognitive load using multiple measures, including…
A plethora of research in the literature shows how human eye fixation pattern varies depending on different factors, including genetics, age, social functioning, cognitive functioning, and so on. Analysis of these variations in visual…
Head-mounted eye trackers promise convenient access to reliable gaze data in unconstrained environments. Due to several limitations, however, often they can only partially deliver on this promise. Among those are the following: (i) the…
Deep learning models are widely recognized for their effectiveness in identifying medical image findings in disease classification. However, their limitations become apparent in the dynamic and ever-changing clinical environment,…
Model-based clustering is a powerful tool that is often used to discover hidden structure in data by grouping observational units that exhibit similar response values. Recently, clustering methods have been developed that permit…
With the development of widely available commercial eye trackers, the use of eye tracking and pupillometry have become prevalent tools in cognitive research, both in industry and academia. However, dealing with pupil recordings often proves…
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…
We formulate a novel technique for the detection of functional clusters in discrete event data. The advantage of this algorithm is that no prior knowledge of the number of functional groups is needed, as our procedure progressively combines…
A new method for clustering functional data is proposed via information maximization. The proposed method learns a probabilistic classifier in an unsupervised manner so that mutual information (or squared loss mutual information) between…
The emergence of mobile eye trackers embedded in next generation smartphones or VR displays will make it possible to trace not only what objects we look at but also the level of attention in a given situation. Exploring whether we can…
Techniques for clustering student behaviour offer many opportunities to improve educational outcomes by providing insight into student learning. However, one important aspect of student behaviour, namely its evolution over time, can often…