The Full-scale Assembly Simulation Testbed (FAST) Dataset
원문 초록
In recent years, numerous researchers have begun investigating how virtual reality (VR) tracking and interaction data can be used for a variety of machine learning purposes, including user identification, predicting cybersickness, and estimating learning gains. One constraint for this research area is the dearth of open datasets. In this paper, we present a new open dataset captured with our VR-based Full-scale Assembly Simulation Testbed (FAST). This dataset consists of data collected from 108 participants (50 females, 56 males, 2 non-binary) learning how to assemble two distinct full-scale structures in VR. In addition to explaining how the dataset was collected and describing the data included, we discuss how the dataset may be used by future researchers.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Energy-Free Sensing and Context Recognition Using Photovoltaic Cells
Versatile User Identification in Extended Reality using Pretrained Similarity-Learning
GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition
Reinforcement Learning-enhanced Shared-account Cross-domain Sequential Recommendation
WiFi-based Multi-task Sensing
Backdoor Attack against Speaker Verification
토론
이 논문과 연결된 포럼 글이 아직 없습니다.