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Download README.md from xentim/fall-detection-sample: direct link, hf CLI and curl.
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metadata
license: other
license_name: xentim-sample-evaluation
license_link: https://xentim.com/datasets/fall-detection/licence.txt
pretty_name: Fall Detection Dataset Sample
task_categories:
- video-classification
tags:
- fall-detection
- pose-estimation
- keypoints
- skeleton
- action-recognition
- synthetic
- cctv
- computer-vision
size_categories:
- n<1K
extra_gated_heading: Get the free Fall Detection Dataset sample
extra_gated_prompt: >-
This sample is for internal evaluation only. See LICENSE.txt. Your details go
to Xentim (TATO STUDIO sp. z o.o.), so we can reply about your evaluation.
Privacy policy https://xentim.com/en/privacy-policy
extra_gated_button_content: Get the sample
extra_gated_fields:
Company or institution: text
Work email: text
Role: text
What will you test it on?: text
I agree to use this sample for internal evaluation only: checkbox
Fall Detection Dataset v1.2: free sample
Free evaluation sample of a synthetic dataset for skeleton-based fall detection and person-down alarms.
Synthetic data: no real people and no personal data.
What is in this sample
- 336 sequences from 28 simulated events
data/frames.parquet: one row per frame and cameradata/index.csv: one row per sequencedata/skeleton3d/: 3D skeletonspreview_videos/: short skeleton previews00_OVERVIEW_*.mp4: overview of the sampleDATASHEET.md: full specification and known limits
This is skeleton data, with no RGB video.
Load it
import pandas as pd
index = pd.read_csv("data/index.csv")
frames = pd.read_parquet("data/frames.parquet")
print(index.head())
Full dataset
12,108 sequences, 2.22 million annotated frames, 20.6 hours at 30 fps, 12 virtual cameras per event, 17 COCO keypoints, bounding box and fall phase per person per frame.
Commercial licence, from 18,000 EUR: Fall Detection Dataset
Licence
Free for internal evaluation only, see LICENSE.txt. Using it in a product needs a paid licence.
Questions or custom data: contact@xentim.com
