HMD-Poser: On-Device Real-time Human Motion Tracking from Scalable
Sparse Observations
- URL: http://arxiv.org/abs/2403.03561v1
- Date: Wed, 6 Mar 2024 09:10:36 GMT
- Title: HMD-Poser: On-Device Real-time Human Motion Tracking from Scalable
Sparse Observations
- Authors: Peng Dai, Yang Zhang, Tao Liu, Zhen Fan, Tianyuan Du, Zhuo Su,
Xiaozheng Zheng, Zeming Li
- Abstract summary: We propose HMD-Poser, the first unified approach to recover full-body motions using scalable sparse observations from HMD and body-worn IMUs.
A lightweight temporal-spatial feature learning network is proposed in HMD-Poser to guarantee that the model runs in real-time on HMDs.
Extensive experimental results on the challenging AMASS dataset show that HMD-Poser achieves new state-of-the-art results in both accuracy and real-time performance.
- Score: 28.452132601844717
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: It is especially challenging to achieve real-time human motion tracking on a
standalone VR Head-Mounted Display (HMD) such as Meta Quest and PICO. In this
paper, we propose HMD-Poser, the first unified approach to recover full-body
motions using scalable sparse observations from HMD and body-worn IMUs. In
particular, it can support a variety of input scenarios, such as HMD,
HMD+2IMUs, HMD+3IMUs, etc. The scalability of inputs may accommodate users'
choices for both high tracking accuracy and easy-to-wear. A lightweight
temporal-spatial feature learning network is proposed in HMD-Poser to guarantee
that the model runs in real-time on HMDs. Furthermore, HMD-Poser presents
online body shape estimation to improve the position accuracy of body joints.
Extensive experimental results on the challenging AMASS dataset show that
HMD-Poser achieves new state-of-the-art results in both accuracy and real-time
performance. We also build a new free-dancing motion dataset to evaluate
HMD-Poser's on-device performance and investigate the performance gap between
synthetic data and real-captured sensor data. Finally, we demonstrate our
HMD-Poser with a real-time Avatar-driving application on a commercial HMD. Our
code and free-dancing motion dataset are available
https://pico-ai-team.github.io/hmd-poser
Related papers
- EMHI: A Multimodal Egocentric Human Motion Dataset with HMD and Body-Worn IMUs [17.864281586189392]
Egocentric human pose estimation (HPE) using wearable sensors is essential for VR/AR applications.
Most methods rely solely on either egocentric-view images or sparse Inertial Measurement Unit (IMU) signals.
We propose EMHI, a multimodal textbfEgocentric human textbfMotion dataset with textbfHead-Mounted Display (HMD) and body-worn textbfIMUs.
arXiv Detail & Related papers (2024-08-30T10:12:13Z) - HMP: Hand Motion Priors for Pose and Shape Estimation from Video [52.39020275278984]
We develop a generative motion prior specific for hands, trained on the AMASS dataset which features diverse and high-quality hand motions.
Our integration of a robust motion prior significantly enhances performance, especially in occluded scenarios.
We demonstrate our method's efficacy via qualitative and quantitative evaluations on the HO3D and DexYCB datasets.
arXiv Detail & Related papers (2023-12-27T22:35:33Z) - HMD-NeMo: Online 3D Avatar Motion Generation From Sparse Observations [7.096701481970196]
Head-Mounted Devices (HMDs) typically only provide a few input signals, such as head and hands 6-DoF.
We propose the first unified approach, HMD-NeMo, that addresses plausible and accurate full body motion generation even when the hands may be only partially visible.
arXiv Detail & Related papers (2023-08-22T08:07:12Z) - QuestSim: Human Motion Tracking from Sparse Sensors with Simulated
Avatars [80.05743236282564]
Real-time tracking of human body motion is crucial for immersive experiences in AR/VR.
We present a reinforcement learning framework that takes in sparse signals from an HMD and two controllers.
We show that a single policy can be robust to diverse locomotion styles, different body sizes, and novel environments.
arXiv Detail & Related papers (2022-09-20T00:25:54Z) - Human POSEitioning System (HPS): 3D Human Pose Estimation and
Self-localization in Large Scenes from Body-Mounted Sensors [71.29186299435423]
We introduce (HPS) Human POSEitioning System, a method to recover the full 3D pose of a human registered with a 3D scan of the surrounding environment.
We show that our optimization-based integration exploits the benefits of the two, resulting in pose accuracy free of drift.
HPS could be used for VR/AR applications where humans interact with the scene without requiring direct line of sight with an external camera.
arXiv Detail & Related papers (2021-03-31T17:58:31Z) - Stochastic-HMDs: Adversarial Resilient Hardware Malware Detectors
through Voltage Over-scaling [3.5803801804085347]
Machine learning-based hardware malware detectors (HMDs) offer a potential game changing advantage in defending systems against malware.
HMDs suffer from adversarial attacks, can be effectively reverse-engineered and subsequently be evaded, allowing malware to hide from detection.
We propose a novel HMDs (Stochastic-HMDs) through approximate computing, which makes HMDs resilient against adversarial evasion attacks.
arXiv Detail & Related papers (2021-03-11T20:18:40Z) - Unmasking Communication Partners: A Low-Cost AI Solution for Digitally
Removing Head-Mounted Displays in VR-Based Telepresence [62.997667081978825]
Face-to-face conversation in Virtual Reality (VR) is a challenge when participants wear head-mounted displays (HMD)
Past research has shown that high-fidelity face reconstruction with personal avatars in VR is possible under laboratory conditions with high-cost hardware.
We propose one of the first low-cost systems for this task which uses only open source, free software and affordable hardware.
arXiv Detail & Related papers (2020-11-06T23:17:12Z) - Augment Yourself: Mixed Reality Self-Augmentation Using Optical
See-through Head-mounted Displays and Physical Mirrors [49.49841698372575]
Optical see-though head-mounted displays (OST HMDs) are one of the key technologies for merging virtual objects and physical scenes to provide an immersive mixed reality (MR) environment to its user.
We propose a novel concept and prototype system that combines OST HMDs and physical mirrors to enable self-augmentation and provide an immersive MR environment centered around the user.
Our system, to the best of our knowledge the first of its kind, estimates the user's pose in the virtual image generated by the mirror using an RGBD camera attached to the HMD and anchors virtual objects to the reflection rather
arXiv Detail & Related papers (2020-07-06T16:53:47Z) - Gaze-Sensing LEDs for Head Mounted Displays [73.88424800314634]
We exploit the sensing capability of LEDs to create low-power gaze tracker for virtual reality (VR) applications.
We show that our gaze estimation method does not require complex dimension reduction techniques.
arXiv Detail & Related papers (2020-03-18T23:03:06Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.