3D skeletons UP-Fall Dataset
Description
3D skeletons UP-Fall Dataset
Different between Fall and Impact detection
Overview
This dataset aims to facilitate research in fall detection, particularly focusing on the precise detection of impact moments within fall events. The 3D skeletons data accuracy and comprehensiveness make it a valuable resource for developing and benchmarking fall detection algorithms. The dataset contains 3D skeletal data extracted from fall events and daily activities of 5 subjects performing fall scenarios
Data Collection
The skeletal data was extracted using a pose estimation algorithm, which processes images frames to determine the 3D coordinates of each joint. Sequences with less than 100 frames of extracted data were excluded to ensure the quality and reliability of the dataset. As a result, some subjects may have fewer CSV files.
CSV Structure
The data is organized by subjects, and each subject contains CSV files named according to the pattern C1S1A1T1, where:
- C: Camera (1 or 2)
- S: Subject (1 to 5)
- A: Activity (1 to N, representing different activities)
- T: Trial (1 to 3)
subject1/`: Contains CSV files for Subject 1.
- C1S1A1T1.csv: Data from Camera 1, Activity 1, Trial 1 for Subject 1
- C1S1A2T1.csv: Data from Camera 1, Activity 2, Trial 1 for Subject 1
- C1S1A3T1.csv: Data from Camera 1, Activity 3, Trial 1 for Subject 1
- C2S1A1T1.csv: Data from Camera 2, Activity 1, Trial 1 for Subject 1
- C2S1A2T1.csv: Data from Camera 2, Activity 2, Trial 1 for Subject 1
- C2S1A3T1.csv: Data from Camera 2, Activity 3, Trial 1 for Subject 1
subject2/`: Contains CSV files for Subject 2.
- C1S2A1T1.csv: Data from Camera 1, Activity 1, Trial 1 for Subject 2
- C1S2A2T1.csv: Data from Camera 1, Activity 2, Trial 1 for Subject 2
- C1S2A3T1.csv: Data from Camera 1, Activity 3, Trial 1 for Subject 2
- C2S2A1T1.csv: Data from Camera 2, Activity 1, Trial 1 for Subject 2
- C2S2A2T1.csv: Data from Camera 2, Activity 2, Trial 1 for Subject 2
- C2S2A3T1.csv: Data from Camera 2, Activity 3, Trial 1 for Subject 2
subject3/, subject4/, subject5/: Similar structure as above, but may contain fewer CSV files due to the data extraction criteria mentioned above.
Column Descriptions
Each CSV file contains the following columns representing different skeletal joints and their respective coordinates in 3D space:
Column Name |
Description |
joint_1_x |
X coordinate of joint 1 |
joint_1_y |
Y coordinate of joint 1 |
joint_1_z |
Z coordinate of joint 1 |
joint_2_x |
X coordinate of joint 2 |
joint_2_y |
Y coordinate of joint 2 |
joint_2_z |
Z coordinate of joint 2 |
... |
... |
joint_n_x |
X coordinate of joint n |
joint_n_y |
Y coordinate of joint n |
joint_n_z |
Z coordinate of joint n |
LABEL |
Label indicating impact (1) or non-impact (0) |
Example
Here is an example of what a row in one of the CSV files might look like:
joint_1_x |
joint_1_y |
joint_1_z |
joint_2_x |
joint_2_y |
joint_2_z |
... |
joint_n_x |
joint_n_y |
joint_n_33 |
LABEL |
0.123 |
0.456 |
0.789 |
0.234 |
0.567 |
0.890 |
... |
0.345 |
0.678 |
0.901 |
0 |
Usage
This data can be used for developing and benchmarking impact fall detection algorithms. It provides detailed information on human posture and movement during falls, making it suitable for machine learning and deep learning applications in impact fall detection and prevention.
Using github
1. Clone the repository:
-bash
git clone
https://github.com/Tresor-Koffi/3D_skeletons-UP-Fall-Dataset
2. Navigate to the directory:
-bash
-cd 3D_skeletons-UP-Fall-Dataset
Examples
Here's a simple example of how to load and inspect a sample data file using Python:
```python
import pandas as pd
# Load a sample data file for Subject 1, Camera 1, Activity 1, Trial 1
data = pd.read_csv('subject1/C1S1A1T1.csv')
print(data.head())
Files
SUBJECT1.zip
Files
(4.0 MB)
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md5:6c34ff6e898b42ecead633836206a5b0
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941.8 kB | Preview Download |
md5:4db506e5a541ad2de84bf5009d440f13
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md5:76a641d4bb79488a0563dde1041f95c8
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Additional details
Dates
- Submitted
-
2024-07-18