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Kenan Bektas
Title
Dr.
Last Name
Bektas
First name
Kenan
Email
kenan.bektas@unisg.ch
ORCID
Phone
+41 71 224 27 63
Google Scholar
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1 - 4 of 4
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PublicationGEAR: Gaze-enabled augmented reality for human activity recognition(ACM, 2023-05-30)
;Hermann, Jonas ;Jenss, Kay ErikSoler, Marc EliasHead-mounted Augmented Reality (AR) displays overlay digital information on physical objects. Through eye tracking, they allow novel interaction methods and provide insights into user attention, intentions, and activities. However, only few studies have used gaze-enabled AR displays for human activity recognition (HAR). In an experimental study, we collected gaze data from 10 users on a HoloLens 2 (HL2) while they performed three activities (i.e., read, inspect, search). We trained machine learning models (SVM, Random Forest, Extremely Randomized Trees) with extracted features and achieved an up to 98.7% activity-recognition accuracy. On the HL2, we provided users with an AR feedback that is relevant to their current activity. We present the components of our system (GEAR) including a novel solution to enable the controlled sharing of collected data. We provide the scripts and anonymized datasets which can be used as teaching material in graduate courses or for reproducing our findings.Type: conference paper -
PublicationEToS-1: Eye Tracking on Shopfloors for User Engagement with Automation(CEUR Workshop Proceedings, 2022-04-30)Stolze, MarkusMixed Reality (MR) is becoming an integral part of many context-aware industrial applications. In maintenance and remote support operations, the individual steps of computer-supported (cooperative) work can be defined and presented to human operators through MR headsets. Tracking of eye movements can provide valuable insights into a user’s decision-making and interaction processes. Thus, our overarching goal is to better understand the visual inspection behavior of machine operators on shopfloors and to find ways to provide them with attention-aware and context-aware assistance through MR headsets that increasingly come with eye tracking (ET) as a default feature. Toward this goal, in two industrial scenarios, we used two mobile eye tracking devices and systematically compared the visual inspection behavior of novice and expert operators. In this paper we present our preliminary findings and lessons learned.Type: conference paper
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PublicationSOCRAR: Semantic OCR through Augmented Reality(ACM, 2022-11-11)To enable people to interact more efficiently with virtual and physical services in their surroundings, it would be beneficial if information could more fluently be passed across digital and non-digital spaces. To this end, we propose to combine semantic technologies with Optical Character Recognition on an Augmented Reality (AR) interface to enable the semantic integration of (written) information located in our everyday environments with Internet of Things devices. We hence present SOCRAR, a system that is able to detect written information from a user’s physical environment while contextualizing this data through a semantic backend. The SOCRAR system enables in-band semantic translation on an AR interface, permits semantic filtering and selection of appropriate device interfaces, and provides cognitive offloading by enabling users to store information for later use. We demonstrate the feasibility of SOCRAR through the implementation of three concrete scenarios.Type: conference paperJournal: Proceedings of the 12th International Conference on the Internet of Things
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PublicationType: conference paper
Scopus© Citations 9