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1st Workshop on Prototyping and Developing Real-World Applications for extended reality, RealXR 2024

作者： Aigner, David Friedl-Knirsch, Judith Anthes, Christoph University of Applied Sciences Austria Technical University of Munich Human-Centered Computing Extended Reality Lab Germany

As novel mixed reality devices are developed, the use case of augmented reality display extension becomes feasible. Especially, in a visual data analysis use case, users can then benefit from expanding the conventional screen space using augmented reality head-mounted displays. This opens up the discussion of suitable placement of user interface elements in this extended augmented reality space. This includes questions about customisability, interaction, and moving elements across the borders of a desktop screen. Therefore, we present design considerations on layout and interaction with augmented reality extended displays and propose a system that employs the discussed techniques to support the data analysis process. © 2022 Copyright for this paper by its authors.

关键词： Augmented reality

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DimSplat: A Real-Time Diminished reality System for Revisiting Environments Using Gaussian Splats in Mobile WebXR

DimSplat: A Real-Time Diminished Reality System for Revisiti...

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Virtual reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Kristoffer Waldow Jonas Scholz Arnulph Fuhrmann Human-Centered-Computing and Extended Reality Lab Technical University Munich TH Köln Computer Graphics Group

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Diminished reality (DR) allows for the selective removal or transformation of real-world objects from a user’s field of view. In certain cases, it becomes essential to revisit environments and observe them in their original state. While Smartphone and Web-based approaches provide intuitive and convenient AR platforms, it also faces challenges like limited resources. This work introduces a DR system using Gaussian splats for real-time object removal on WebXR-enabled devices. We achieve up to 60 FPS while maintaining high visual fidelity, validated with different image quality metrics, offering a scalable solution for revisiting and manipulating temporally altered environments.

关键词： Measurement Image quality Visualization Three-dimensional displays Virtual reality User interfaces Rendering (computer graphics) Real-time systems Mobile handsets Faces

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DimSplat: A Real-Time Diminished reality System for Revisiting Environments Using Gaussian Splats in Mobile WebXR

DimSplat: A Real-Time Diminished Reality System for Revisiti...

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2025 IEEE Conference on Virtual reality and 3D User Interfaces Abstracts and Workshops, VRW 2025

作者： Waldow, Kristoffer Scholz, Jonas Fuhrmann, Arnulph Th Köln Computer Graphics Group Germany Technical University Munich Human-Centered-Computing and Extended Reality Lab Germany

ISBN: (纸本)9798331514846

Diminished reality (DR) allows for the selective removal or transformation of real-world objects from a user's field of view. In certain cases, it becomes essential to revisit environments and observe them in their original state. While Smartphone and Web-based approaches provide intuitive and convenient AR platforms, it also faces challenges like limited resources. This work introduces a DR system using Gaussian splats for real-time object removal on WebXR-enabled devices. We achieve up to 60 FPS while maintaining high visual fidelity, validated with different image quality metrics, offering a scalable solution for revisiting and manipulating temporally altered environments. © 2025 IEEE.

关键词： Rendering (computer graphics)

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Semantics-Controlled Gaussian Splatting for Outdoor Scene Reconstruction and Rendering in Virtual reality 32

Semantics-Controlled Gaussian Splatting for Outdoor Scene Re...

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32nd IEEE Conference on Virtual reality and 3D User Interfaces, VR 2025

作者： Schieber, Hannah Young, Jacob Langlotz, Tobias Zollmann, Stefanie Roth, Daniel Technical University of Munich Human-Centered Computing and Extended Reality Lab Tum University Hospital Clinic for Orthopedics and Sports Orthopedics Munich Germany Erlangen Germany University of Otago Department of Computer Science Dunedin New Zealand Aarhus University Department of Computer Science Aarhus Denmark

ISBN: (纸本)9798331536459

Advancements in 3D rendering like Gaussian Splatting (GS) allow novel view synthesis and real-time rendering in virtual reality (VR). However, GS-created 3D environments are often difficult to edit. For scene enhancement or to incorporate 3D assets, segmenting Gaussians by class is essential. Existing segmentation approaches are typically limited to certain types of scenes, e.g., "circular"scenes, to determine clear object boundaries. However, this method is ineffective when removing large objects in non-"circling"scenes such as large outdoor *** propose Semantics-Controlled GS (SCGS), a segmentation-driven GS approach, enabling the separation of large scene parts in uncontrolled, natural environments. SCGS allows scene editing and the extraction of scene parts for VR. Additionally, we introduce a challenging outdoor dataset, overcoming the "circling"setup. We outperform the state-of-the-art in visual quality on our dataset and in segmentation quality on the 3D-OVS dataset. We conducted an exploratory user study, comparing a 360-video, plain GS, and SCGS in VR with a fixed viewpoint. In our subsequent main study, users were allowed to move freely, evaluating plain GS and SCGS. Our main study results show that participants clearly prefer SCGS over plain GS. We overall present an innovative approach that surpasses the state-of-the-art both technically and in user experience. © 2025 IEEE.

关键词： Virtual environments

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A Modular Approach for 3D Reconstruction with Point Cloud Overlay

A Modular Approach for 3D Reconstruction with Point Cloud Ov...

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2023 IEEE International Symposium on Mixed and Augmented reality Adjunct, ISMAR-Adjunct 2023

作者： Schieber, Hannah Schmid, Fritz Mubashir-Ui-Hassan Zollmann, Stefanie Roth, Daniel Human-Centered Computing and Extended Reality Germany University of Otago Department of Computer Science Dunedin New Zealand Technical University of Munich School of Medicine and Health Klinikum Rechts der Isar Orthopaedics and Sports Orthopaedics Germany

ISBN: (纸本)9798350328912

Integrating the real-world through the power of 3D reconstruction plays an essential role in extended reality teleconsultation. Video streams and voxel-based representations are common techniques for teleconsultation visualization. However, video streaming applications miss 3D content information, and voxel-based representation can only provide visual details with increasing computational costs. To enhance the classical voxel-based representation and address the timeliness of voxels, we present a modular approach which provides a point cloud overlay to highlight the latest update in the current camera frustum. Our approach applies state-of-the-art algorithms and custom packages within ROS to enable 3D reconstruction with dynamic cameras. We present a modular approach allowing the flexible exchange of the individual part, i.e. the camera or SLAM algorithm. This work presents results from a pilot study involving five participants to gain an impression of what kind of visualization type would be preferred and whether the point cloud overlay would assist the user in recognizing changes in the surroundings. The point cloud overlay enabled the participants to perceive more changes. The pilot study revealed that 60% of the participants showed a preference for the point cloud overlay over the pure mesh representation. © 2023 IEEE.

关键词： Cameras

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ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation 23

ASDF: Assembly State Detection Utilizing Late Fusion by Inte...

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23rd IEEE International Symposium on Mixed and Augmented reality, ISMAR 2024

作者： Schieber, Hannah Li, Shiyu Corell, Niklas Beckerle, Philipp Kreimeier, Julian Roth, Daniel Technical University of Munich Human-Centered Computing and Extended Reality Lab TUM School of Medicine and Health TUM School of Computation Information and Technology Clinic for Orthopedics and Sports Orthopedics TUM University Hospital Munich Germany Erlangen-Nürnberg Department Artificial Intelligence in Biomedical Engineering Erlangen Germany Erlangen-Nürnberg Chair of Autonomous Systems and Mechatronics Erlangen Germany

ISBN: (纸本)9798331516475

In medical and industrial domains, providing guidance for assembly processes can be critical to ensure efficiency and safety. Errors in assembly can lead to significant consequences such as extended surgery times and prolonged manufacturing or maintenance times in industry. Assembly scenarios can benefit from in-situ augmented reality visualization, i.e., augmentations in close proximity to the target object, to provide guidance, reduce assembly times, and minimize errors. In order to enable in-situ visualization, 6D pose estimation can be leveraged to identify the correct location for an augmentation. Existing 6D pose estimation techniques primarily focus on individual objects and static captures. However, assembly scenarios have various dynamics, including occlusion during assembly and dynamics in the appearance of assembly objects. Existing work focus either on object detection combined with state detection, or focus purely on the pose estimation. To address the challenges of 6D pose estimation in combination with assembly state detection, our approach ASDF builds upon the strengths of YOLOv8, a real-time capable object detection framework. We extend this framework, refine the object pose, and fuse pose knowledge with network-detected pose information. Utilizing our late fusion in our Pose2State module results in refined 6D pose estimation and assembly state detection. By combining both pose and state information, our Pose2State module predicts the final assembly state with precision. The evaluation of our ASDF dataset shows that our Pose2State module leads to an improved assembly state detection and that the improvement of the assembly state further leads to a more robust 6D pose estimation. Moreover, on the GBOT dataset, we outperform the pure deep learning-based network and even outperform the hybrid and pure tracking-based approaches. © 2024 IEEE.

关键词： Augmented reality

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Semantics-Controlled Gaussian Splatting for Outdoor Scene Reconstruction and Rendering in Virtual reality

arXiv

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arXiv 2024年

作者： Schieber, Hannah Young, Jacob Langlotz, Tobias Zollmann, Stefanie Roth, Daniel Erlangen Germany Department of Computer Science University of Otago Dunedin New Zealand Technical University of Munich Human-Centered Computing and Extended Reality Lab TUM University Hospital Orthopedics and Sports Orthopedics Germany

Advancements in 3D rendering like Gaussian Splatting (GS) allow novel view synthesis and real-time rendering in virtual reality (VR). However, GS-created 3D environments are often difficult to edit. For scene enhancement or to incorporate 3D assets, segmenting Gaussians by class is essential. Existing segmentation approaches are typically limited to certain types of scenes, e.g., "circular" scenes, to determine clear object boundaries. However, this method is ineffective when removing large objects in non-"circling" scenes such as large outdoor scenes. We propose Semantics-Controlled GS (SCGS), a segmentationdriven GS approach, enabling the separation of large scene parts in uncontrolled, natural environments. SCGS allows scene editing and the extraction of scene parts for VR. Additionally, we introduce a challenging outdoor dataset, overcoming the "circling" setup. We outperform the state-of-the-art in visual quality on our dataset and in segmentation quality on the 3D-OVS dataset. We conducted an exploratory user study, comparing a 360-video, plain GS, and SCGS in VR with a fixed viewpoint. In our subsequent main study, users were allowed to move freely, evaluating plain GS and SCGS. Our main study results show that participants clearly prefer SCGS over plain GS. We overall present an innovative approach that surpasses the state-of-the-art both technically and in user experience. © 2024, CC BY.

关键词： Virtual environments

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Indoor Synthetic Data Generation: A Systematic Review

SSRN

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SSRN 2023年

作者： Schieber, Hannah Demir, Kubilay Can Kleinbeck, Constantin Yang, Seung Hee Roth, Daniel Human-Centered Computing and Extended Reality Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Speech and Language Processing Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany

Objective: Deep learning-based object recognition, 6D pose estimation, and semantic scene understanding requires a large amount of training data to achieve generalization. Time-consuming annotation processes, privacy, and security aspects lead to a scarcity of real-world datasets. To overcome this lack of data, synthetic data generation has been proposed, including multiple facets in the area of domain randomization to extend the data distribution. The objective of this review is to identify methods applied for synthetic data generation aiming to improve 6D pose estimation, object recognition, and semantic scene understanding in indoor scenarios. We further review methods used to extend the data distribution and discuss best practices to bridge the gap between synthetic and real-world data. Methods: We adhered to the guidelines of the systematic PRISMA technique. Three databases, IEEE Xplore, Springer Link, and ACM, and an additional manual search are conducted. In total, we identified 241 studies and included 34 in our systematic review. Conclusion: In summary, synthetic data generation has been performed using crop-out methods, graphic APIs, 3D modeling of authoring tools, or game engine-based methods. To extend the data distribution, varying scene parameters, i.e., lighting conditions or textures and the use of distracting objects in the scene are promising. © 2023, The Authors. All rights reserved.

关键词： Object recognition

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ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation

arXiv

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arXiv 2024年

作者： Schieber, Hannah Li, Shiyu Corell, Niklas Beckerle, Philipp Kreimeier, Julian Roth, Daniel Technical University of Munich Human-Centered Computing and Extended Reality Lab TUM School of Medicine Health TUM School of Computation Information and Technology Clinic for Orthopedics and Sports Orthopedics TUM University Hospital Munich Germany Erlangen-Nürnberg Erlangen Germany Erlangen-Nürnberg Erlangen Germany

关键词： Visualization

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Investigating the Effects of Selective Information Presentation in Intensive Care Units Using Virtual reality

Investigating the Effects of Selective Information Presentat...

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International Symposium on Mixed and Augmented reality (ISMAR)

作者： Luisa Theelke Fynn-Lennardt Metzler Julian Kreimeier Christopher Hauer Johannes Binder Daniel Roth Human-Centered Computing and Extended Reality Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Universitätsklinikum Erlangen School of Medicine and Health Klinikum rechts der Isar Orthopaedics and Sports Orthopaedics Technical University of Munich

Medical personnel working in intensive care units (ICUs) are continuously exposed to a multitude of alarms emanating from various monitoring devices, such as cardiac monitors, ventilators, or infusion pumps. The sheer volume of alarms, coupled with high false positive rates, can lead to alarm fatigue. This phenomenon compromises patient safety and places an additional burden on nurses who must diligently prioritize and respond to alarms in the highly dynamic environment. While the testing of stress-reducing strategies in a real ICU is challenging, virtual reality (VR) represents a powerful tool and methodology to simulate an ICU environment and test optimization scenarios for alarm display strategies. For example, redistributing alarms to responsible individuals (personalized information presentation) has been proposed as a solution, but testing in real ICU environments is not applicable due to critical patient safety. In this paper, we present a VR simulation of an ICU to simulate comparable stress situations, as well as to assess the impact of a selective and personalized alarm representation strategy in an evaluation study in two conditions. A stress condition mirrors the current ubiquitous audible alarm distribution in most ICUs, where alarms are heard non-patient-specific throughout the ward. In an experimental condition, alarms are filtered patient-specific to reduce information overload and noise pollution. Our user study with medical personnel and novices shows that stress levels can be simulated with our system as indicated by physiological responses. Further, we show that the perceived task load can be reduced with selective information presentation. We discuss the potential benefits of ICU simulations as a methodology and personalized alarm distribution as a first potential strategy for future technologies in ICUs.

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