Animation Fidelity in Self-Avatars: Impact on User Performance and Sense of Agency

The use of self-avatars is gaining popularity thanks to affordable VR headsets. Unfortunately, mainstream VR devices often use a small number of trackers and provide low-accuracy animations. Previous studies have shown that the Sense of Embodiment, and in particular the Sense of Agency, depends on the extent to which the avatar's movements mimic the user's movements. However, few works study such effect for tasks requiring a precise interaction with the environment, i.e., tasks that require accurate manipulation, precise foot stepping, or correct body poses. In these cases, users are likely to notice inconsistencies between their self-avatars and their actual pose. In this paper, we study the impact of the animation fidelity of the user avatar on a variety of tasks that focus on arm movement, leg movement and body posture. We compare three different animation techniques: two of them using Inverse Kinematics to reconstruct the pose from sparse input (6 trackers), and a third one using a professional motion capture system with 17 inertial sensors. We evaluate these animation techniques both quantitatively (completion time, unintentional collisions, pose accuracy) and qualitatively (Sense of Embodiment). Our results show that the animation quality affects the Sense of Embodiment. Inertial-based MoCap performs significantly better in mimicking body poses. Surprisingly, IK-based solutions using fewer sensors outperformed MoCap in tasks requiring accurate positioning, which we attribute to the higher latency and the positional drift that causes errors at the end-effectors, which are more noticeable in contact areas such as the feet.Comment: Accepted in IEEE VR 202

Learning data-driven character animation

Real-time animation of virtual characters has traditionally been accomplished by playing short sequences of animations structured in the form of a graph. These methods are time-consuming to set up and scale poorly with the number of motions required in modern virtual environments. The ever-increasing need for highly-realistic virtual characters in fields such as entertainment, virtual reality, or the metaverse has led to significant advances in the field of data-driven character animation. Techniques like Motion Matching have provided enough versatility to conveniently animate virtual characters using a selection of features from an animation database. Data-driven methods retain the quality of the captured animations, thus delivering smoother and more natural-looking animations. In this work, we researched and developed a Motion Matching technique for the Unity game engine. In this thesis, we present our findings on how to implement an animation system based on Motion Matching. We also introduce a novel method combining body orientation prediction with Motion Matching to animate avatars for consumer-grade virtual reality systems

SparsePoser: Real-time Full-body Motion Reconstruction from Sparse Data

<p>Data used for the paper <strong>SparsePoser: Real-time Full-body Motion Reconstruction from Sparse Data</strong></p> <p>It contains over <strong>1GB</strong> of high-quality<strong> motion capture data</strong> recorded with an Xsens Awinda system while using a variety of <strong>VR applications</strong> in Meta Quest devices.</p> <p>Visit the paper <a href="https://upc-virvig.github.io/SparsePoser/">website</a>!</p> <p> </p> <p><strong>If you find our data useful, please cite our paper:</strong></p> <p>@article{10.1145/3625264, author = {Ponton, Jose Luis and Yun, Haoran and Aristidou, Andreas and Andujar, Carlos and Pelechano, Nuria}, title = {SparsePoser: Real-Time Full-Body Motion Reconstruction from Sparse Data}, year = {2023}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, issn = {0730-0301}, url = {https://doi.org/10.1145/3625264}, doi = {10.1145/3625264}, journal = {ACM Trans. Graph.}, month = {oct}}</p&gt

BJS commission on surgery and perioperative care post-COVID-19

Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues' experiences and published evidence

BJS commission on surgery and perioperative care post-COVID-19

Background: Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues experiences and published evidence. Methods: In late 2020, BJS contacted colleagues across the global surgical community and asked them to describe how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had affected their practice. In addition to this, the Commission undertook a literature review on the impact of COVID-19 on surgery and perioperative care. A thematic analysis was performed to identify the issues most frequently encountered by the correspondents, as well as the solutions and ideas suggested to address them. Results: BJS received communications for this Commission from leading clinicians and academics across a variety of surgical specialties in every inhabited continent. The responses from all over the world provided insights into multiple facets of surgical practice from a governmental level to individual clinical practice and training. Conclusion: The COVID-19 pandemic has uncovered a variety of problems in healthcare systems, including negative impacts on surgical practice. Global surgical multidisciplinary teams are working collaboratively to address research questions about the future of surgery in the post-COVID-19 era. The COVID-19 pandemic is severely damaging surgical training. The establishment of a multidisciplinary ethics committee should be encouraged at all surgical oncology centres. Innovative leadership and collaboration is vital in the post-COVID-19 era