Showing papers by "Morten Fjeld published in 2021"
06 May 2021
TL;DR: In this paper, the authors conducted an in-depth interview study with 10 professional drone pilots, armed with significant experience and qualifications relevant to both drone operations and a set of applications covering diverse industries.
Abstract: Human-drone interaction is a growing topic of interest within HCI research. Researchers propose many innovative concepts for drone applications, but much of this research does not incorporate knowledge on existing applications already adopted by professionals. This limits the validity of said research. To address this limitation, we present our findings from an in-depth interview study with 10 professional drone pilots. Our participants were armed with significant experience and qualifications – pertinent to both drone operations and a set of applications covering diverse industries. Our findings have resulted in design recommendations that should inform both ends and means of human-drone interaction research. These include, but are not limited to: safety-related protocols, insights from domain-specific use cases, and relevant practices outside of hands-on flight.
15 citations
21 Sep 2021
TL;DR: In this article, the authors report an initial prototype supporting complex data visualization and analysis in entire 3D surroundings within industrial process tomography (IPT), which is equipped for users to interact with the 3D information characterizing the workflow of the industrial process with high immersion.
Abstract: Today, in-situ analyzing and monitoring are imperative for ensuring successful and healthy industrial processes in confined environments. With the rapid development of digitization, augmented reality (AR) has been utilized for letting people immersively interact with the necessary information. However, there are still knowledge gaps between AR technique and domain users pertaining to effective analysis of complex data. Hence, new solutions empowering domain users would benefit the whole industry. In this study, we report an initial prototype supporting complex data visualization and analysis in entire 3D surroundings within industrial process tomography (IPT). Microsoft HoloLens 2 is equipped for users to interact with the 3D information characterizing the workflow of the industrial process with high immersion. Our work distinctly improves the performance compared to existing solutions, pointing the way towards how AR should be deployed and developed more efficiently for aiding IPT systems.
8 citations
TL;DR: In this article, an up-to-date augmented reality (AR) technique is proposed to support the corresponding data visualization and on-site analysis for industrial microwave drying systems. But the proposed AR system is integrated with the on-going process data, including reconstructed, segmented, and volumetric images, which are used for facilitating interactive onsite data analysis.
Abstract: Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this article, we propose a complete data processing and visualizing workflow regarding a specific case—microwave tomography (MWT) controlled industrial microwave drying system. Furthermore, we present the up-to-date augmented reality (AR) technique to support the corresponding data visualization and on-site analysis. As a pioneering study of using AR to benefit IPT systems, the proposed AR module provides straightforward and comprehensible visualizations pertaining to the process data to the related users. Inside the dataflow of the case, a time reversal imaging algorithm, a post-imaging segmentation, and a volumetric visualization module are included. For the time reversal algorithm, we exhaustively introduce each step for MWT image reconstruction and then present the simulated results. For the post-imaging segmentation, an automatic tomographic segmentation algorithm is utilized to reveal the significant information contained in the reconstructed images. For volumetric visualization, the 3D generated information is displayed. Finally, the proposed AR system is integrated with the on-going process data, including reconstructed, segmented, and volumetric images, which are used for facilitating interactive on-site data analysis for domain users. The central part of the AR system is implemented by a mobile app that is currently supported on iOS/Android platforms.
8 citations
TL;DR: In this article, the authors presented the same colormaps within a crowdsourced study comprising two parts to verify the quantitative outcomes, the first part encoded affective responses from participants into a prevailing four-quadrant valence-arousal grid; the second part recorded participant ratings towards the accuracy of each colormap on MWT segmentation.
Abstract: The design of colormaps can help tomography operators obtain accurate visual comprehension, thereby assisting safety-critical decisions. The research presented here is about deploying colormaps that promote the best affective responses for industrial microwave tomography (MWT). To answer the two research questions related to our study, we firstly conducted a quantitative analysis of 11 frequently-used colormaps on a segmentation task. Secondly, we presented the same colormaps within a crowdsourced study comprising two parts to verify the quantitative outcomes. The first part encoded affective responses from participants into a prevailing four-quadrant valence-arousal grid; the second part recorded participant ratings towards the accuracy of each colormap on MWT segmentation. We concluded that three colormaps are the best suited in the context of MWT tasks. We also found that the colormaps triggering emotions in the positive-exciting quadrant can facilitate more accurate visual comprehension than other affect-related quadrants. A synthetic colormap design guideline was consequently proposed.
6 citations
28 Jun 2021
TL;DR: In this paper, the authors explored the design of VXSlate, an interaction technique that uses a large virtual display as an expansion of a tablet, and combined a user head movements as tracked by the VR headset and touch interaction on the tablet.
Abstract: Virtual Reality (VR) headsets can open opportunities for users to accomplish complex tasks on large virtual displays using compact and portable devices. However, interacting with such large virtual displays using existing interaction techniques might cause fatigue, especially for precise manipulation tasks, due to the lack of physical surfaces. To deal with this issue, we explored the design of VXSlate, an interaction technique that uses a large virtual display as an expansion of a tablet. We combined a user’s head movements as tracked by the VR headset, and touch interaction on the tablet. Using VXSlate, a user head movements positions a virtual representation of the tablet together with the user’s hand, on the large virtual display. This allows the user to perform fine-tuned multi-touch content manipulations. In a user study with seventeen participants, we investigated the effects of VXSlate on users in problem-solving tasks involving content manipulations at different levels of difficulty, such as translation, rotation, scaling, and sketching. As a baseline for comparison, off-the-shelf touch-controller interactions were used. Overall, VXSlate allowed participants to complete the task with completion times and accuracy that are comparable to touch-controller interactions. After an interval of use, VXSlate significantly reduced users’ time to perform scaling tasks in content manipulations, as well as reducing perceived effort. We reflected on the advantages and disadvantages of VXSlate in content manipulation on large virtual displays and explored further applications within the VXSlate design space.
4 citations
28 May 2021
TL;DR: In this article, the authors explored how to effectively exploit deep learning in affective colormaps within the domain of industrial tomography, and proposed a convolutional neural network (CNN) consisting of 10 layers reached high recognition and prediction accuracy in the colormap-affect relationship.
Abstract: Humans show different emotions in response to variant colormaps when facing visual presentations. The affect—colormap relationship thus becomes an important factor in human-in-the-loop systems. In this paper, we explore how to effectively exploit deep learning in affective colormaps within the domain of industrial tomography. Eleven pervasively used colormaps were picked as the stimuli, followed by a user study which gathered data on the human affect of each colormap as well as benchmarking our initial dataset. The affect was encoded into an emotional model over two dimensions; valence (positive—negative), and arousal (exciting—calm). Our proposed convolutional neural network (CNN) consisting of 10 layers reached high recognition and prediction accuracy in the colormap—affect relationship. The obtained results affirmed our exploration, which could in future assist developers to construct more intelligent and reliable human-computer interaction (HCI) systems.
4 citations
27 Mar 2021
TL;DR: VXSlate is designed, an interaction technique that uses a large virtual display, as an expansion of a tablet, that combines a user’s head movements, as tracked by the VR headset, and touch interaction on the tablet.
Abstract: Virtual Reality (VR) headsets can open opportunities for users to accomplish complex tasks on large virtual displays, using compact setups. However, interacting with large virtual displays using existing interaction techniques might cause fatigue, especially for precise manipulations, due to the lack of physical surfaces. We designed VXSlate, an interaction technique that uses a large virtual display, as an expansion of a tablet. VXSlate combines a user’s head movements, as tracked by the VR headset, and touch interaction on the tablet. The user’s head movements position both a virtual representation of the tablet and of the user’s hand on the large virtual display. The user’s multi-touch interactions perform finely-tuned content manipulations.
TL;DR: VXSlate as discussed by the authors combines a user's head movement, as tracked by the VR headset, and touch interaction on the tablet to perform fine-tuned content manipulations on large virtual displays.
Abstract: Virtual Reality (VR) headsets can open opportunities for users to accomplish complex tasks on large virtual displays, using compact setups. However, interacting with large virtual displays using existing interaction techniques might cause fatigue, especially for precise manipulations, due to the lack of physical surfaces. We designed VXSlate, an interaction technique that uses a large virtual display, as an expansion of a tablet. VXSlate combines a user's headmovement, as tracked by the VR headset, and touch interaction on the tablet. The user's headmovement position both a virtual representation of the tablet and of the user's hand on the large virtual display. The user's multi-touch interactions perform finely-tuned content manipulations.