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Khalad Hasan

Publications and source records attributed to Khalad Hasan.

9 recordsLinked to original sources

Leveraging Head Movement for Navigating Off-Screen Content on Large Curved Displays

Large curved displays are ideal for viewing 360 degree content, such as 3D maps, but typically restrict users to a 180 degree viewport, leaving information off-screen. Since users naturally direct their heads toward regions on-screen before interacting, head movements offer a promising alternative for workspace manipulation to bring off-screen content into view. We explore rate control functions (linear, sigmoid, polynomial) and zone control functions (continuous, friction, interrupted, additive) to translate head rotations into workspace control, enabling users to access off-screen content. Polynomial rate control emerges as the best choice, achieving the fastest trial times and highest subjective ratings. Using a map navigation task, our second study demonstrates that users perform better with the polynomial head-based technique than with the industry-standard controller-based methods, click-and-drag and joystick-push, for 360\degree workspace navigation. Based on these findings, we provide guidelines to inform the design of future 360\degree workspace navigation techniques for large curved displays.

cs.HC

Are You Comfortable Sharing It?: Leveraging Image Obfuscation Techniques to Enhance Sharing Privacy for Blind and Visually Impaired Users

People with Blind Visual Impairments (BVI) face unique challenges when sharing images, as these may accidentally contain sensitive or inappropriate content. In many instances, they are unaware of the potential risks associated with sharing such content, which can compromise their privacy and interpersonal relationships. To address this issue, we investigated image filtering techniques that could help BVI users manage sensitive content before sharing with various audiences, including family, friends, or strangers. We conducted a study with 20 BVI participants, evaluating different filters applied to images varying in sensitivity, such as personal moments or embarrassing shots. Results indicated that pixelation was the least preferred method, while preferences for other filters varied depending on image type and sharing context. Additionally, participants reported greater comfort when sharing filtered versus unfiltered images across audiences. Based on the results, we offer a set of design guidelines to enhance the image-sharing experience for BVI individuals.

cs.HC

Position: Universal Aesthetic Alignment Narrows Artistic Expression

Over-aligning image generation models to a generalized aesthetic preference conflicts with user intent, particularly when "anti-aesthetic" outputs are requested for artistic or critical purposes. This adherence prioritizes developer-centered values, compromising user autonomy and aesthetic pluralism. We test this bias by constructing a wide-spectrum aesthetics dataset and evaluating state-of-the-art generation and reward models. This position paper finds that aesthetic-aligned generation models frequently default to conventionally beautiful outputs, failing to respect instructions for low-quality or negative imagery. Crucially, reward models penalize anti-aesthetic images even when they perfectly match the explicit user prompt. We confirm this systemic bias through image-to-image editing and evaluation against real abstract artworks. Our code, fine-tuned models, and datasets are available on our meta-expression intentionally anti-aesthetics webpage: https://weathon.github.io/icml2026_position/.

cs.CY

Exploring the Effect of Viewing Attributes of Mobile AR Interfaces on Remote Collaborative and Competitive Tasks

Mobile devices have the potential to facilitate remote tasks through Augmented Reality (AR) solutions by integrating digital information into the real world. Although prior studies have explored Mobile Augmented Reality (MAR) for co-located collaboration, none have investigated the impact of various viewing attributes that can influence remote task performance, such as target object viewing angles, synchronization styles, or having a secondary small screen showing other users current view in the MAR environment. In this paper, we explore five techniques considering these attributes, specifically designed for two modes of remote tasks: collaborative and competitive. We conducted a user study employing various combinations of those attributes for both tasks. In both instances, results indicate users' optimal performance and preference for the technique that allows asynchronous viewing of object manipulations on the small screen. Overall, this paper contributes novel techniques for remote tasks in MAR, addressing aspects such as viewing angle and synchronization in object manipulation alongside secondary small-screen interfaces. Additionally, it presents the results of a user study evaluating the effectiveness, usability, and user preference of these techniques in remote settings and offers a set of recommendations for designing and implementing MAR solutions to enhance remote activities.

cs.HC

Exploring Pointer Enhancement Techniques for Target Selection on Large Curved Display

Large curved displays are becoming increasingly popular due to their ability to provide users with a wider field of view and a more immersive experience compared to flat displays. Current interaction techniques for large curved displays often assume a user is positioned at the display's centre, crucially failing to accommodate general use conditions where the user may move during use. In this work, we investigated how user position impacts pointing interaction on large curved displays and evaluated cursor enhancement techniques to provide faster and more accurate performance across positions. To this effect, we conducted two user studies. First, we evaluated the effects of user position on pointing performance on a large semi-circular display (3m-tall, 3270R curvature) through a 2D Fitts' Law selection task. Our results indicate that as users move away from the display, their pointing speed significantly increases (at least by 9%), but accuracy decreases (by at least 6%). Additionally, we observed participants were slower when pointing from laterally offset positions. Secondly, we explored which pointing techniques providing motor- and visual-space enhancements best afford effective pointing performance across user positions. Across a total of six techniques tested, we found that a combination of acceleration and distance-based adjustments with cursor enlargement significantly improves target selection speed and accuracy across different user positions. Results further show techniques with visual-space enhancements (e.g., cursor enlargement) are significantly faster and more accurate than their non-visually-enhanced counterparts. Based on our results we provide design recommendations for implementing cursor enhancement techniques for large curved displays.

cs.HC

Exploring Bi-Manual Teleportation in Virtual Reality

Teleportation, a widely-used locomotion technique in Virtual Reality (VR), allows instantaneous movement within VR environments. Enhanced hand tracking in modern VR headsets has popularized hands-only teleportation methods, which eliminate the need for physical controllers. However, these techniques have not fully explored the potential of bi-manual input, where each hand plays a distinct role in teleportation: one controls the teleportation point and the other confirms selections. Additionally, the influence of users' posture, whether sitting or standing, on these techniques remains unexplored. Furthermore, previous teleportation evaluations lacked assessments based on established human motor models such as Fitts' Law. To address these gaps, we conducted a user study (N=20) to evaluate bi-manual pointing performance in VR teleportation tasks, considering both sitting and standing postures. We proposed a variation of the Fitts' Law model to accurately assess users' teleportation performance. We designed and evaluated various bi-manual teleportation techniques, comparing them to uni-manual and dwell-based techniques. Results showed that bi-manual techniques, particularly when the dominant hand is used for pointing and the non-dominant hand for selection, enable faster teleportation compared to other methods. Furthermore, bi-manual and dwell techniques proved significantly more accurate than uni-manual teleportation. Moreover, our proposed Fitts' Law variation more accurately predicted users' teleportation performance compared to existing models. Finally, we developed a set of guidelines for designers to enhance VR teleportation experiences and optimize user interactions.

cs.HC

Exploring Users Pointing Performance on Large Displays with Different Curvatures in Virtual Reality

Large curved displays inside Virtual Reality environments are becoming popular for visualizing high-resolution content during analytical tasks, gaming or entertainment. Prior research showed that such displays provide a wide field of view and offer users a high level of immersion. However, little is known about users' performance (e.g., pointing speed and accuracy) on them. We explore users' pointing performance on large virtual curved displays. We investigate standard pointing factors (e.g., target width and amplitude) in combination with relevant curve-related factors, namely display curvature and both linear and angular measures. Our results show that the less curved the display, the higher the performance, i.e., faster movement time. This result holds for pointing tasks controlled via their visual properties (linear widths and amplitudes) or their motor properties (angular widths and amplitudes). Additionally, display curvatures significantly affect the error rate for both linear and angular conditions. Furthermore, we observe that curved displays perform better or similar to flat displays based on throughput analysis. Finally, we discuss our results and provide suggestions regarding pointing tasks on large curved displays in VR.

cs.HC

Exploring Users' Pointing Performance on Virtual and Physical Large Curved Displays

Large curved displays have emerged as a powerful platform for collaboration, data visualization, and entertainment. These displays provide highly immersive experiences, a wider field of view, and higher satisfaction levels. Yet, large curved displays are not commonly available due to their high costs. With the recent advancement of Head Mounted Displays (HMDs), large curved displays can be simulated in Virtual Reality (VR) with minimal cost and space requirements. However, to consider the virtual display as an alternative to the physical display, it is necessary to uncover user performance differences (e.g., pointing speed and accuracy) between these two platforms. In this paper, we explored users' pointing performance on both physical and virtual large curved displays. Specifically, with two studies, we investigate users' performance between the two platforms for standard pointing factors such as target width, target amplitude as well as users' position relative to the screen. Results from user studies reveal no significant difference in pointing performance between the two platforms when users are located at the same position relative to the screen. In addition, we observe users' pointing performance improves when they are located at the center of a semi-circular display compared to off-centered positions. We conclude by outlining design implications for pointing on large curved virtual displays. These findings show that large curved virtual displays are a viable alternative to physical displays for pointing tasks.

cs.HC

Exploration of Hands-free Text Entry Techniques For Virtual Reality

Text entry is a common activity in virtual reality (VR) systems. There is a limited number of available hands-free techniques, which allow users to carry out text entry when users' hands are busy such as holding items or hand-based devices are not available. The most used hands-free text entry technique is DwellType, where a user selects a letter by dwelling over it for a specific period. However, its performance is limited due to the fixed dwell time for each character selection. In this paper, we explore two other hands-free text entry mechanisms in VR: BlinkType and NeckType, which leverage users' eye blinks and neck's forward and backward movements to select letters. With a user study, we compare the performance of the two techniques with DwellType. Results show that users can achieve an average text entry rate of 13.47, 11.18 and 11.65 words per minute with BlinkType, NeckType, and DwellType, respectively. Users' subjective feedback shows BlinkType as the preferred technique for text entry in VR.

cs.HC