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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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…

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…

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…

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…

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…

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…

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…