Summary of Synthetic Multimodal Dataset For Empowering Safety and Well-being in Home Environments, by Takanori Ugai et al.
Synthetic Multimodal Dataset for Empowering Safety and Well-being in Home Environments
by Takanori Ugai, Shusaku Egami, Swe Nwe Nwe Htun, Kouji Kozaki, Takahiro Kawamura, Ken Fukuda
First submitted to arxiv on: 26 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces a novel multimodal dataset combining 3D virtual space simulator video data with knowledge graphs capturing daily activities’ spatial-temporal context. The goal is to facilitate the development of innovative solutions for identifying hazardous situations at home, as part of the Knowledge Graph Reasoning Challenge for Social Issues (KGRC4SI). The proposed dataset enables researchers and practitioners to recognize human behaviors and enhance safety and well-being. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a special kind of computer data that mixes videos from a pretend 3D world with information about what’s happening in those scenes. This data is useful for finding ways to keep people safe at home, which is an important problem. The data can be used by experts who want to make new solutions to help people stay safe and happy. |
Keywords
» Artificial intelligence » Knowledge graph
