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Humans only recognize a few items in a scene at once and memorize three to seven items in the short term. Such limitations can be mitigated using cognitive offloading (e.g., sticky notes, digital reminders). We studied whether a gaze-enabled Augmented Reality (AR) system could facilitate cognitive offloading and improve object retrieval performance. To this end, we developed NeighboAR, which detects objects in a user's surroundings and generates a graph that stores object proximity relationships and user's gaze dwell times for each object. In a controlled experiment, we asked N=17 participants to inspect randomly distributed objects and later recall the position of a given target object. Our results show that displaying the target together with the proximity object with the longest user gaze dwell time helps recalling the position of the target. Specifically, NeighboAR significantly reduces the retrieval time by 33%, number of errors by 71%, and perceived workload by 10%.

Aleksandar Slavuljica, Kenan Bektaş, Jannis Strecker, and Simon Mayer. 2024. NeighboAR: Efficient Object Retrieval using Proximity- and Gaze-based Object Grouping with an AR System. Proc. ACM Hum.-Comput. Interact. 8, ETRA, Article 225 (May 2024), 19 pages. https://doi.org/10.1145/3655599

@inproceedings{slavuljica2024,
author = {Slavuljica, Aleksandar and Bekta\c{s}, Kenan and Strecker, Jannis and Mayer, Simon},
title = {NeighboAR: Efficient Object Retrieval using Proximity-and Gaze-based Object Grouping with an AR System},
year = {2024},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://www.alexandria.unisg.ch/handle/20.500.14171/119906},
doi = {10.1145/3655599},
abstract = {Humans only recognize a few items in a scene at once and memorize three to seven items in the short term. Such limitations can be mitigated using cognitive offloading (e.g., sticky notes, digital reminders). We studied whether a gaze-enabled Augmented Reality (AR) system could facilitate cognitive offloading and improve object retrieval performance. To this end, we developed NeighboAR, which detects objects in a user's surroundings and generates a graph that stores object proximity relationships and user's gaze dwell times for each object. In a controlled experiment, we asked N=17 participants to inspect randomly distributed objects and later recall the position of a given target object. Our results show that displaying the target together with the proximity object with the longest user gaze dwell time helps recalling the position of the target. Specifically, NeighboAR significantly reduces the retrieval time by 33%, number of errors by 71%, and perceived workload by 10%.},
booktitle = {Proc. ACM Hum.-Comput. Interact.},
volume = {8}
issue = {ETRA},
articleno = {225},
numpages = {19},
keywords = {augmented reality, cognitive offloading, eye tracking, object detection,human augmentation, mixed reality, working memory, visual search},
}

Non-communicable diseases, such as obesity and diabetes, have a significant global impact on health outcomes. While governments worldwide focus on promoting healthy eating, individuals still struggle to follow dietary recommendations. Augmented Reality (AR) might be a useful tool to emphasize specific food products at the point of purchase. However, AR may also add visual clutter to an already complex supermarket environment. Instead, reducing the visual prevalence of unhealthy food products through Diminished Reality (DR) could be a viable alternative: We present Shopping-Coach, a DR prototype that identifies supermarket food products and visually diminishes them dependent on the deviation of the target product’s composition from dietary recommendations. In a study with 12 participants, we found that ShoppingCoach increased compliance with dietary recommendations from 75% to 100% and reduced decision time by 41%. These results demonstrate the promising potential of DR in promoting healthier food choices and thus enhancing public health.

Jannis Strecker, Jing Wu, Kenan Bektaş, Conrad Vaslin, and Simon Mayer. 2024. ShoppingCoach: Using Diminished Reality to Prevent Unhealthy Food Choices in an Offline Supermarket Scenario. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3613905.3650795

@inproceedings{strecker2024,
title = {{{ShoppingCoach}}: {{Using Diminished Reality}} to {{Prevent Unhealthy Food Choices}} in an {{Offline Supermarket Scenario}}},
booktitle = {Extended {{Abstracts}} of the {{CHI Conference}} on {{Human Factors}} in {{Computing Systems}} ({{CHI EA}} '24)},
author = {Strecker, Jannis and Wu, Jing and Bekta{\c s}, Kenan and Vaslin, Conrad and Mayer, Simon},
year = {2024},
langid = {english},
doi = {10.1145/3613905.3650795},
publisher = {ACM},
location = {Honolulu, HI, USA},
series = {CHI EA '24}
}

As QR codes become ubiquitous in various applications and places, their susceptibility to tampering, known as quishing, poses a significant threat to user security. In this paper we introduce SafeQR codes that address this challenge by introducing innovative design strategies to enhance QR code security. Leveraging visual elements and secure design principles, the project aims to make tampering more noticeable, thereby empowering users to recognize and avoid potential phishing threats. Further, we highlight the limitations of current user-education methods in combating quishing and propose different attacker models tailored to address quishing attacks. In addition, we introduce a multi-faceted defense strategy that merges design innovation with user vigilance. Through a user study, we demonstrate the efficacy of ’Integrity by Design’ QR codes. These innovatively designed QR codes significantly raise user suspicion in case of tampering and effectively reduce the likelihood of successful quishing attacks.

Luka Bekavac, Simon Mayer, and Jannis Strecker. 2024. QR Code Integrity by Design. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3613905.3651006

@inproceedings{strecker2024,
title = {{QR Code Integrity by Design}},
booktitle = {Extended {{Abstracts}} of the {{CHI Conference}} on {{Human Factors}} in {{Computing Systems}} ({{CHI EA}} '24)},
author = {Bekavac, Luka and Mayer, Simon and Strecker, Jannis},
year = {2024},
langid = {english},
doi = {10.1145/3613905.3651006},
publisher = {ACM},
location = {Honolulu, HI, USA},
series = {CHI EA '24}
}