A small parallel Croatian-English corpus was analyzed in order to study the role of implicit prosody in silent reading. Croatian and English are well suited for this purpose with English having a stress-timed prosody and Croatian being more of a syllable-...

This paper aims to advance the fields of unsupervised data labeling and incremental cross-domain training techniques. We apply these innovative methods to develop a model tailored for the Augmentative and Alternative Communication (AAC) application ...

This study shows a method for estimating users’ emotions in Virtual Reality (VR) spaces through the collection of eye behaviors. In our method, we use eye-related information available from the Head Mounted Display (HMD), including the direction vector ...

Appearance-based gaze tracking algorithms, which compute gaze direction from user face images, are an attractive alternative to infrared-based external devices. Their accuracy has greatly benefited by using powerful machine-learning techniques. The ...

When presented with the same question about an image, human annotators often give valid but disagreeing answers indicating that their reasoning was different. Such differences are lost in a single ground truth label used to train and evaluate visual ...

Preserving cultural heritage is paramount for societal and historical identity. Paintings, spanning ancient to modern eras, are pivotal subjects under constant scrutiny. As art reflects human creativity, studying human visual behavior toward paintings ...

Chess is known worldwide and has acquired a deep cultural significance. It is recognized as a sport by the International Olympic Committee, and this sport has around 600 million players worldwide. Since chess is a strategic game, it requires an estimate ...

In eye tracking, the most promising approaches for person identification are based on the iris. Therefore, the iris of a subject is extracted and compared against a database of stored iris templates or directly classified by a deep neural network. While ...

The human gaze is increasingly used for different applications in interactive systems. It is used for explicit and implicit user input detection and is suitable for various purposes, such as activation commands, emotion detection, or user ...

We introduce the Webcam Eye Dataset (WEyeDS) 1, a dataset of images collected from desktops and laptops. WEyeDS will be openly available with the goal of providing researchers a dataset for training gaze estimation models. Our preliminary dataset was ...

Cognitive training can boost and sharpen the brain’s abilities to remember, focus, and switch between different tasks. One of the key elements of cognitive training is cognitive load. It allows a manipulation of the intensity of the intervention to suit ...

In eye tracking, pupil detection is a crucial step for gaze estimation. While there are a plethora of datasets with accurate annotations, new devices, such as differently placed cameras, usually require more data to be annotated since the new ...

Eyelid detection is an important feature for fatigue estimation in autonomous driving, for example. It allows for the estimation of driver readiness if a takeover event occurs, and is therefore crucial for the safety of car passengers and traffic ...

The advancement of image restoration, especially in reconstructing missing or damaged image areas, has benefited significantly from self-supervised learning techniques, notably through the recent Masked Auto Encoder (MAE) strategy. In this project, we ...

Eye tracking is a promising technique to measure gaze direction on food while eating that can be used as a tool to asses eating habits and disorders. However, the studies done as yet use high-quality (infrared) eye trackers under controlled lab ...

Eye movements are a key part of increasing our understanding of human vision and the oculomotor system as they are an excellent proxy for attention. It is for this reason studies exploring task-based eye movements and the relationships between said tasks ...

This paper presents an innovative approach to gaze tracking in the context of smart eyewear, utilizing a fully event-based algorithm. Traditional gaze-tracking methods often rely on grayscale or infrared imaging, which can be computationally intensive ...

Eye-tracking applications that utilize the human gaze in video understanding tasks have become increasingly important. To effectively automate the process of video analysis based on eye-tracking data, it is important to accurately replicate human gaze ...

Prior research states that frequencies below 75 Hz in eye-tracking data represent the primary eye movement termed “signal” while those above 75 Hz are deemed “noise”. This study examines the biometric significance of this signal-noise distinction and ...

This paper presents a novel Contrastive Self-Attention Convolutional Neural Network (CSA-CNN) model with enhanced Difficulty Aware (DA) loss function to improve the segmentation of pupils in eye images. The incorporation of transformer-style self-...