Zobrazeno 1 - 10
of 218
pro vyhledávání: '"Schmitt, Syn"'
Human hand and head movements are the most pervasive input modalities in extended reality (XR) and are significant for a wide range of applications. However, prior works on hand and head modelling in XR only explored a single modality or focused on s
Externí odkaz:
http://arxiv.org/abs/2410.16430
We present HOIMotion - a novel approach for human motion forecasting during human-object interactions that integrates information about past body poses and egocentric 3D object bounding boxes. Human motion forecasting is important in many augmented r
Externí odkaz:
http://arxiv.org/abs/2407.02633
We present GazeMotion, a novel method for human motion forecasting that combines information on past human poses with human eye gaze. Inspired by evidence from behavioural sciences showing that human eye and body movements are closely coordinated, Ga
Externí odkaz:
http://arxiv.org/abs/2403.09885
Autor:
Charaja, Jhon, Wochner, Isabell, Schumacher, Pierre, Ilg, Winfried, Giese, Martin, Maufroy, Christophe, Bulling, Andreas, Schmitt, Syn, Haeufle, Daniel F. B.
The mimicking of human-like arm movement characteristics involves the consideration of three factors during control policy synthesis: (a) chosen task requirements, (b) inclusion of noise during movement execution and (c) chosen optimality principles.
Externí odkaz:
http://arxiv.org/abs/2402.13949
Human motion prediction is important for many virtual and augmented reality (VR/AR) applications such as collision avoidance and realistic avatar generation. Existing methods have synthesised body motion only from observed past motion, despite the fa
Externí odkaz:
http://arxiv.org/abs/2312.12090
Human eye gaze plays a significant role in many virtual and augmented reality (VR/AR) applications, such as gaze-contingent rendering, gaze-based interaction, or eye-based activity recognition. However, prior works on gaze analysis and prediction hav
Externí odkaz:
http://arxiv.org/abs/2312.12042
Autor:
Schumacher, Pierre, Geijtenbeek, Thomas, Caggiano, Vittorio, Kumar, Vikash, Schmitt, Syn, Martius, Georg, Haeufle, Daniel F. B.
Humans excel at robust bipedal walking in complex natural environments. In each step, they adequately tune the interaction of biomechanical muscle dynamics and neuronal signals to be robust against uncertainties in ground conditions. However, it is s
Externí odkaz:
http://arxiv.org/abs/2309.02976
In the context of embodied artificial intelligence, morphological computation refers to processes, which are conducted by the body (and environment) that otherwise would have to be performed by the brain. Exploiting environmental and morphological pr
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A83692
https://ul.qucosa.de/api/qucosa%3A83692/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A83692/attachment/ATT-0/
Autor:
Wochner, Isabell, Schumacher, Pierre, Martius, Georg, Büchler, Dieter, Schmitt, Syn, Haeufle, Daniel F. B.
Humans are able to outperform robots in terms of robustness, versatility, and learning of new tasks in a wide variety of movements. We hypothesize that highly nonlinear muscle dynamics play a large role in providing inherent stability, which is favor
Externí odkaz:
http://arxiv.org/abs/2207.03952
Muscle-actuated organisms are capable of learning an unparalleled diversity of dexterous movements despite their vast amount of muscles. Reinforcement learning (RL) on large musculoskeletal models, however, has not been able to show similar performan
Externí odkaz:
http://arxiv.org/abs/2206.00484