arXiv · 2401.14743
Synthetic Multimodal Dataset for Empowering Safety and Well-being in Home Environments
Abstract
This paper presents a synthetic multimodal dataset of daily activities that fuses video data from a 3D virtual space simulator with knowledge graphs depicting the spatiotemporal context of the activities. The dataset is developed for the Knowledge Graph Reasoning Challenge for Social Issues (KGRC4SI), which focuses on identifying and addressing hazardous situations in the home environment. The dataset is available to the public as a valuable resource for researchers and practitioners developing innovative solutions recognizing human behaviors to enhance safety and well-being in
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Takanori Ugai, Shusaku Egami, Swe Nwe Nwe Htun, Kouji Kozaki, Takahiro Kawamura, Ken Fukuda. 2024-01-26. Synthetic Multimodal Dataset for Empowering Safety and Well-being in Home Environments. https://arxiv.org/abs/2401.14743
Cite the original work for its findings. Save a collection to share your selection of sources.