Temporal RIT-Eyes: From Real Infrared Eye-Images to Synthetic Sequences of Gaze Behavior.

Current methods for segmenting eye imagery into skin, sclera, pupil, and iris cannot leverage information about eye motion. This is because the datasets on which models are trained are limited to temporally non-contiguous frames. We present Temporal RIT-Eyes, a Blender pipeline that draws data from real eye videos for the rendering of synthetic imagery depicting natural gaze dynamics.

EllSeg: An Ellipse Segmentation Framework for Robust Gaze Tracking.

Ellipse fitting, an essential component in pupil or iris tracking based video oculography, is performed on previously segmented eye parts generated using various computer vision techniques. Several factors, such as occlusions due to eyelid shape, camera position or eyelashes, frequently break ellipse fitting algorithms that rely on well-defined pupil or iris edge segments. In this work, we propose training a convolutional neural network to directly segment entire elliptical structures and demonstrate that such a framework is robust to occlusions and offers superior pupil and iris tracking performance (at least 10% and 24% increase in pupil and iris center detection rate respectively within a two-pixel error margin) compared to using standard eye parts segmentation for multiple publicly available synthetic segmentation datasets.

Computational framework for fusing eye movements and spoken narratives for image annotation.

Despite many recent advances in the field of computer vision, there remains a disconnect between how computers process images and how humans understand them. To begin to bridge this gap, we propose a framework that integrates human-elicited gaze and spoken language to label perceptually important regions in an image. Our work relies on the notion that gaze and spoken narratives can jointly model how humans inspect and analyze images.

Gaze-in-wild: A dataset for studying eye and head coordination in everyday activities.

The study of gaze behavior has primarily been constrained to controlled environments in which the head is fixed. Consequently, little effort has been invested in the development of algorithms for the categorization of gaze events (e.g.

From lab-based studies to eye-tracking in virtual and real worlds: conceptual and methodological problems and solutions. Symposium 4 at the 20th European Conference on Eye Movement Research (ECEM) in Alicante, 20.8.2019.

Wearable mobile eye trackers have great potential as they allow the measurement of eye movements during daily activities such as driving, navigating the world and doing groceries. Although mobile eye trackers have been around for some time, developing and operating these eye trackers was generally a highly technical affair. As such, mobile eye-tracking research was not feasible for most labs.

Motion tracking of iris features to detect small eye movements.

The inability of current video-based eye trackers to reliably detect very small eye movements has led to confusion about the prevalence or even the existence of monocular microsaccades (small, rapid eye movements that occur in only one eye at a time). As current methods often rely on precisely localizing the pupil and/or corneal reflection on successive frames, current microsaccade-detection algorithms often suffer from signal artifacts and a low signal-to-noise ratio. We describe a new video-based eye tracking methodology which can reliably detect small eye movements over 0.

Eye tracking to evaluate evidence recognition in crime scene investigations.

Crime scene analysts are the core of criminal investigations; decisions made at the scene greatly affect the speed of analysis and the quality of conclusions, thereby directly impacting the successful resolution of a case. If an examiner fails to recognize the pertinence of an item on scene, the analyst's theory regarding the crime will be limited. Conversely, unselective evidence collection will most likely include irrelevant material, thus increasing a forensic laboratory's backlog and potentially sending the investigation into an unproductive and costly direction.

Modeling eye movement patterns to characterize perceptual skill in image-based diagnostic reasoning processes.

Experts have a remarkable capability of locating, perceptually organizing, identifying, and categorizing objects in images specific to their domains of expertise. In this article, we present a hierarchical probabilistic framework to discover the stereotypical and idiosyncratic viewing behaviors exhibited with expertise-specific groups. Through these patterned eye movement behaviors we are able to elicit the domain-specific knowledge and perceptual skills from the subjects whose eye movements are recorded during diagnostic reasoning processes on medical images.

A study of artificial eyes for the measurement of precision in eye-trackers.

The precision of an eye-tracker is critical to the correct identification of eye movements and their properties. To measure a system's precision, artificial eyes (AEs) are often used, to exclude eye movements influencing the measurements. A possible issue, however, is that it is virtually impossible to construct AEs with sufficient complexity to fully represent the human eye.

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

Objectives: Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge.

Predictive eye movements in natural vision.

In the natural world, the brain must handle inherent delays in visual processing. This is a problem particularly during dynamic tasks. A possible solution to visuo-motor delays is prediction of a future state of the environment based on the current state and properties of the environment learned from experience.

Eye tracking users of a visual diagnostic clinical decision support system to discover decision-making strategies and to inform user interface design.

Clinical decision support systems (CDSS) assist physicians and other medical professionals in tasks such as differential diagnosis. End users may use different decision-making strategies depending on medical training. Study of eye movements reveals information processing strategies that are executed at a level below consciousness.

Learning via direct and mediated instruction by deaf students.

Four experiments investigated classroom learning by deaf college students receiving lectures from instructors signing for themselves or using interpreters. Deaf students' prior content knowledge, scores on postlecture assessments of content learning, and gain scores were compared to those of hearing classmates. Consistent with prior research, deaf students, on average, came into and left the classroom with less content knowledge than hearing peers, and use of simultaneous communication (sign and speech together) and American Sign Language (ASL) apparently were equally effective for deaf students' learning of the material.

Monitoring eye movements to investigate the picture superiority effect in spatial memory.

Spatial memory is usually better for iconic than for verbal material. Our aim was to assess whether such effect is related to the way iconic and verbal targets are viewed when people have to memorize their locations. Eye movements were recorded while participants memorized the locations of images or words.

Classroom Interpreting and Visual Information Processing in Mainstream Education for Deaf Students: Live or Memorex?

This study examined visual information processing and learning in classrooms including both deaf and hearing students. Of particular interest were the effects on deaf students' learning of live (three-dimensional) versus video-recorded (two-dimensional) sign language interpreting and the visual attention strategies of more and less experienced deaf signers exposed to simultaneous, multiple sources of visual information. Results from three experiments consistently indicated no differences in learning between three-dimensional and two-dimensional presentations among hearing or deaf students.

Visual memory and motor planning in a natural task.

This paper investigates the temporal dependencies of natural vision by measuring eye and hand movements while subjects made a sandwich. The phenomenon of change blindness suggests these temporal dependencies might be limited. Our observations are largely consistent with this, suggesting that much natural vision can be accomplished with "just-in-time" representations.