With the rapid growth of digital textual content, users face increasing challenges in rediscovering information which they have encountered in the past. Traditional search engines lack the ability to prioritize content truly viewed by users over merely visible content. We propose a method that captures both text passages and corresponding gaze data while reading, storing them in a searchable knowledge base. We then explore boosting strategies to improve text retrieval by prioritizing passages that users actually viewed, improving the personalization and relevance of search results. To this end, we repurposed the recent g-Rel-READER dataset to evaluate various gaze-based boosting techniques and address the research gap caused by the lack of combined text, gaze, and relevance data. The evaluation demonstrates the potential of gaze data to serve as a boosting criterion for search, with mean average precision (MAP) increased by over 33% over a purely text-based retrieval.
Expanding an object’s region in motor space (selection area) using Voronoi tessellation can facilitate the selection of small targets in gaze-based interfaces. While visual feedforward, such as visualizing the selection area, has been shown to improve selection performance in hand-based interfaces, its influence on gaze-based interfaces remains unclear. To address this, we conducted two user studies to examine how visual feedforward affects fixation behavior and selection performance when the centers of a target and its selection area differ. The results reveal that visualizing either the selection area or its center effectively guides users’ gaze toward the center of the selection area, thereby improving selection accuracy. Furthermore, displaying a gaze cursor reduces errors by enabling users to adjust their fixation, even though it does not directly guide gaze toward the center of the selection area.
We present the Eye2Head Gesture (E2H), a gaze-based technique that integrates saccade gestures with eye-head coordination for target selection in virtual reality. It involves a back-and-forth saccadic gesture, aligning the gaze with the head forward direction and then returning to the target to complete the selection. The first study identified the parameters for implementing the E2H technique, including visualization of the relay zone (i.e., the area anchor to the head’s forward direction), relay zone size, and saccade gesture duration. Four variants of the E2H were developed, each differing in the shape and timing of the relay zone. The second study evaluated four E2H variants against Dwell and Eye&Head techniques, revealing that Region-shaped variant of E2H outperformed others in speed, error, and fatigue. This work contributes a gaze-based technique that harnesses eye-head coordination, using saccadic gestures to enhance the efficiency of target selection, particularly for those at large angular distances.
Recent advances in extended reality (XR) have enabled seamless access to immersive services. However, user authentication in these environments typically relies on conventional methods, such as PIN entry, which remains vulnerable to unauthorized use. This paper investigates gaze behavior as an implicit second authentication factor in XR. Using a Meta Quest Pro headset, participants performed legitimate and impostor login attempts while their gaze data were recorded. Temporal, spatial, and oculomotor metrics revealed distinctive and reproducible gaze dynamics between user roles. Tree-based machine learning models, particularly XGBoost, reliably distinguished legitimate from impostor sessions under user-independent validation (AUC =.84). Calibrating model thresholds further enabled adaptive balancing between security and usability. These findings demonstrate that gaze dynamics can unobtrusively enhance PIN authentication, introducing an adaptive layer that aligns authentication sensitivity with situational risk and user needs in immersive environments.
This eye-tracking study examines saccadic latency during subtitled video processing, i.e., the time to shift attention from the video image to the subtitle, based on subtitle speed (145 vs. 180 words per minute–wpm) and number of lines (one vs. two). We employed a mixed-design experiment with deaf (N=20) and hearing (N=20) participants, making use of a linear mixed-model regression for analysis. While the group difference was not statistically significant, the results revealed a significant interaction between subtitle speed and number of lines: at fast speeds (180 wpm), subtitle line count did not affect latency, yet at slow speeds (145 wpm), two-line subtitles incurred a significantly shorter latency. These findings indicate that two-line subtitles, especially at slower speeds, reduce processing latency, which may preserve more time for actual text comprehension.
