Install modified Logitech QuickCam Express / Go / Chat in Windows 7 / 8 / 10 (32bit, 64bit, x86, x86_64, amd64) without driver signature

How to install an old Logitech QuickCam Express in Windows 10, 64Bit (January 2021) ELCH2 plattform Logitech V-UAP9Logitech QuickCam ExpressUSB 046D Logitech, Inc. 0928 QuickCam ExpressELCH2 Chip Trouble installing patched/unsigned Windows 10 (Version January 2021) drivers – “The hash for the file is not present …” The hash for the file is not present in the specified catalog file. The file is likely corrupt or the victim of tampering. Select the “Start” button.Type “startup”.Select “Change advanced startup settings“.Select “Restart now” under the “Advanced startup” area.Select “Troubleshoot“.Select “Advanced Options“.Select “Startup Options“.Select “Restart“.Press “7” on your keyboard to choose “Disable driver signing…

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Real-Time Gait Reconstruction For Virtual Reality Using a Single Sensor

Feigl T., Gruner L., Mutschler C., and Roth D.: In: International Symposium on Mixed and Augmented Reality (ISMAR), Ipojuca, Pernambuco, 2020.
Mobile VR systems are limited to the motion sensing of head-mounted displays (HMDs) and typically cannot reconstruct the motion of the lower extremities and control the avatar animation. We propose an approach to reconstruct gait motions from a single head-mounted accelerometer. Our experiments show that, an BLSTM approach is the most accurate. Our user study with 21 test subjects examined the effects of our approach on simulator sickness and showed significantly less negative effects on disorientation.
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A Sense of Quality for Augmented Reality Assisted Process Guidance

Redzepagic A., Löffler C., Feigl T., Mutschler C.:In: International Symposium on Mixed and Augmented Reality (ISMAR), Ipojuca, Pernambuco, 2020.The ongoing automation of modern production processes requires novel human-computer interaction concepts that support employees in dealing with the unstoppable increase in time pressure, cognitive load, and the required fine-grained and process-specific knowledge. Augmented Reality (AR) systems support employees by guiding and teaching work processes. Such systems still lack a precise process quality analysis (monitoring), which is, however, crucial to close gaps in the quality assurance of industrial processes. We combine inertial sensors, mounted on work tools, with AR headsets to enrich modern assistance systems with…

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RNN-aided Human Velocity Estimation from a Single IMU

Feigl T., Kram S., Woller P., Siddiqui RH., Philippsen M., Mutschler C.:In: MDPI Sensors Journal 20(13), 2020. Pedestrian Dead Reckoning (PDR) uses inertial measurement units (IMUs) and combines velocity and orientation estimates to determine a position. The estimation of the velocity is still challenging, as the integration of noisy acceleration and angular speed signals over a long period of time causes large drifts. Classic approaches to estimate the velocity optimize for specific applications, sensor positions, and types of movement and require extensive parameter tuning. Our novel hybrid filter combines a convolutional neural network (CNN) and a bidirectional recurrent neural network (BLSTM) (that extract spatial features from the…

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ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization

Ott F., Feigl T., Löffler C., Mutschler C.:In: The IEEE Computer Vision Foundation (CVF), Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Joint Workshop on Long-Term Visual Localization, Visual Odometry and Geometric and Learning-based SLAM, Seattle, Washington, 2020. Visual Odometry (VO) accumulates a positional drift in long-term robot navigation tasks. Although Convolutional Neural Networks (CNNs) improve VO in various aspects, VO still suffers from moving obstacles, discontinuous ob- servation of features, and poor textures or visual informa- tion. While recent approaches estimate a 6DoF pose ei- ther directly from (a series of) images or by merging depth maps with optical flow (OF), research…

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Localization Limitations of ARCore, ARKit, and Hololens in Dynamic Large-Scale Industry Environments

Feigl T., Porada A., Steiner S., Löffler C., Mutschler C., Philippsen M.:In: Proceedings of the 15th International Conference on Computer Graphics Theory and Applications (GRAPP), Valetta, Malta, 2020.Augmented Reality (AR) systems are envisioned to soon be used as smart tools across many Industry 4.0 scenarios. The main promise is that such systems will make workers more productive when they can obtain additional situationally coordinated information both seemlessly and hands-free. This paper studies the ap- plicability of today’s popular AR systems (Apple ARKit, Google ARCore, and Microsoft Hololens) in such an industrial context (large area of 1,600m2, long walking distances of 60m between cubicles, and dynamic environments with volatile…

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Visual-Odometry-aided Pose Regression for 6DoF Camera Localization

Ott F., Feigl T., Löffler C., Mutschler C.:In: arXiv:1912.08263 [cs.CV], 2019.Visual Odometry (VO) accumulates a positional drift in long-term robot navigation tasks. Although Convolutional Neural Networks (CNNs) improve VO in various aspects, VO still suffers from moving obstacles, discontinuous observation of features, and poor textures or visual information. While recent approaches estimate a 6DoF pose either directly from (a series of) images or by merging depth maps with optical flow (OF), research that combines absolute pose regression with OF is limited. We propose ViPR, a novel modular architecture for long-term 6DoF VO that leverages temporal information and synergies between absolute pose estimates (from PoseNet-like…

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UWB Channel Impulse Responses for Positioning in Complex Environments: A Detailed Feature Analysis

Kram S., Stahlke M., Feigl T., Seitz J., Thielecke J.:In: MDPI Sensors Journal, 19(24), 2019.Radio signal-based positioning in environments with complex propagation paths is a challenging task for classical positioning methods. For example, in a typical industrial environment, objects such as machines and workpieces cause reflections, diffractions, and absorptions, which are not taken into account by classical lateration methods and may lead to erroneous positions. Only a few data-driven methods developed in recent years can deal with these irregularities in the propagation paths or use them as additional information for positioning. These methods exploit the channel impulse responses (CIR) that are detected by ultra-wideband radio systems…

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A Bidirectional LSTM for Estimating Dynamic Human Velocities from a Single IMU

Feigl T., Kram S., Woller P., Siddiqui R. H., Philippsen M., Mutschler C.:In: Proceedings of the 10th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Pisa, Italy, 2019. The main challenge in estimating human velocity from noisy Inertial Measurement Units (IMUs) are the errors that accumulate by integrating noisy accelerometer signals over a long time. Known approaches that work on step length esti- mation are optimized for a specific application, sensor position, and movement type, require an exhaustive (manual) parameter tuning, and can thus not be applied to other movement types or to a broader range of applications. Moreover, varying dynamics (as they are present for…

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A Framework for Location-Based VR Applications

Lugrin J. L., Kern F., Kleinbeck C., Roth D., Daxer C., Feigl T., Mutschler C., Latoschik M. E.:GI VR/AR Workshop 2019 (Fulda, 17.09.2019 - 18.09.2019)In: Gesellschaft für Informatik Virtuelle und Erweiterte Realitat: 16. Workshop der GI-Fachgruppe VR/AR Berichte aus der Informatik (GI VR/AR), Fulda, Germany, 2019. This paper presents a framework to develop and investigate location-based Virtual Reality (VR) applications. We demonstrate our framework by introducing a novel type of VR museum, designed to support a large number of simultaneous co-located users. These visitors are walking in a hangar-scale tracking zone (600 m2), while sharing a ten times bigger virtual space (7000 m2). Co-located VR applications like this one are opening novel VR perspectives.…

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