Data · dataset · 2025
Exocentric view hand interaction dataset
Listed in Teesside University Research Data Repository
The dataset provides data exclusively on the exocentric view (third-person view), captured using a Google Pixel 6a smartphone.
Description
The dataset contains 7,221 frame images extracted from original videos recorded under real-world conditions. The images are in PNG format.
The data was taken in various lighting environments, including natural light, white light, yellow light, and dim light, which are best for dynamic applications. The dataset features two, three, and four persons engaged in interactive gameplay activities of Ludo, Poker, and Snakes and Ladders. The dataset includes diverse hand gestures with challenging cases such as motion blur, severe deformation, sharp shadows, and extremely dim lighting conditions.
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This dataset provides original, unprocessed data suitable for researchers to use in training, validation, and testing of supervised, semi-supervised, unsupervised, and self-supervised deep learning models for both static analysis and real-time interaction scenarios. Dataset collection: • Source Location: Rampura, Dhaka, Bangladesh. • Capture
Method
Google Pixel 6a smartphone camera. • Anonymization: All data were rigorously anonymized to maintain confidentiality and privacy. • Consent: All participants provided informed consent for research use. Dataset composition: • Total Participants: 4 Male aged 20 years or older.
Links
Where it is published
- DOI doi.org/10.17632/9d37m3nfgm.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Artificial intelligence · Computer Science & AI · Deep learning · Earth & Environmental Science · Human-computer interaction
- Inferred from text
- Image 65%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/9d37m3nfgm.2 | 7 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:460806 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Human-Computer Interaction'] |
| concepts[field].anzsrc:field:461103 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Deep Learning'] |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |