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Fast and robust pupil detection is an essential prerequisite for video-based eye-tracking in real-world settings. Several algorithms for image-based pupil detection have been proposed, their applicability is mostly limited to laboratory…
Visual grounding, which aims to build a correspondence between visual objects and their language entities, plays a key role in cross-modal scene understanding. One promising and scalable strategy for learning visual grounding is to utilize…
Vessel segmentation of retinal images is a key diagnostic capability in ophthalmology. This problem faces several challenges including low contrast, variable vessel size and thickness, and presence of interfering pathology such as…
Real-time, accurate, and robust pupil detection is an essential prerequisite to enable pervasive eye-tracking and its applications -- e.g., gaze-based human computer interaction, health monitoring, foveated rendering, and advanced driver…
This dissertation advances the state of the art for AR/VR tracking systems by increasing the tracking frequency by orders of magnitude and proposes an efficient algorithm for the problem of edge-aware optimization. AR/VR is a natural way of…
This study evaluates a smartphone-based, deep-learning eye-tracking algorithm by comparing its performance against a commercial infrared-based eye tracker, the Tobii Pro Nano. The aim is to investigate the feasibility of appearance-based…
This paper proposes an eye tracking module for the XR Space Framework aimed at enhancing human performance in XR-based applications, specifically in training, screening, and teleoperation. This framework provides a methodology and…
We present a novel object tracking scheme that can track rigid objects in real time. The approach uses subpixel-precise image edges to track objects with high accuracy. It can determine the object position, scale, and rotation with…
We present a set of results obtained with an innovative eye-tracker based on magnetic dipole localization by means of an array of magnetoresistive sensors. The system tracks both head and eye movements with a high rate (100-200 Sa/s) and in…
Real-time object pose estimation and tracking is challenging but essential for emerging augmented reality (AR) applications. In general, state-of-the-art methods address this problem using deep neural networks which indeed yield…
Conventional feature-based and model-based gaze estimation methods have proven to perform well in settings with controlled illumination and specialized cameras. In unconstrained real-world settings, however, such methods are surpassed by…
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…
Webcam eye tracking for the collection of gaze data in the context of user studies is convenient - it can be used in remote tests where participants do not need special hardware. The approach has strong limitations, especially regarding the…
Augmented Reality (AR) applications often require robust real-time tracking of objects in the user's environment to correctly overlay virtual content. Recent advances in computer vision have produced highly accurate deep learning-based…
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…
Purpose. We present a new method to evaluate the accuracy of an eye tracker based eye localization system. Measuring the accuracy of an eye tracker's primary intention, the estimated point of gaze, is usually done with volunteers and a set…
Gaze-tracking is a novel way of interacting with computers which allows new scenarios, such as enabling people with motor-neuron disabilities to control their computers or doctors to interact with patient information without touching screen…
Human eye gaze estimation is an important cognitive ingredient for successful human-robot interaction, enabling the robot to read and predict human behavior. We approach this problem using artificial neural networks and build a modular…
Object tracking has been broadly applied in unmanned aerial vehicle (UAV) tasks in recent years. However, existing algorithms still face difficulties such as partial occlusion, clutter background, and other challenging visual factors.…
The accurate tracking of live cells using video microscopy recordings remains a challenging task for popular state-of-the-art image processing based object tracking methods. In recent years, several existing and new applications have…