OctoNet Multi-Modal Dataset

Welcome to the OctoNet multi-modal dataset! This dataset provides a variety of human activity recordings from multiple sensor modalities, enabling advanced research in activity recognition, pose estimation, multi-modal data fusion, and more.

1. Overview

• Name: OctoNet
• Data: Multi-modal sensor data, including:
  • Inertial measurement unit (IMU) data
  • Motion capture data in CSV and .npy formats
  • mmWave / Radar data (vayyar_pickle)
  • Multiple sensor nodes (node_1, node_2, etc.) capturing different data streams
• Use Cases:
  • Human activity recognition
  • Human pose estimation
  • Multi-modal signal processing
  • Machine learning/deep learning model training

2. File Organization

The dataset is divided according to the recording nodes. Node 1 contains

3. Automated Download, Merge & Extract Script

To facilitate selective downloads on specific modalities, the files are uniformly named [nodeID]_[modalityName]_[environmentID]_[userID]_[activityName]_[trialID]_[timestamp].[filetype]. Users can utilize the download script (streaming.py) to download files matching specific filename patterns.

4. Directory Structure

After downloading the full dataset, you should have a directory named octonet with a structure similar to:

.
└── octonet
    ├── node_1               # Multi-modal sensor node 1
    ├── node_2               # Multi-modal sensor node 2
    ├── node_3               # Multi-modal sensor node 3
    ├── node_4               # Multi-modal sensor node 4
    ├── node_5               # Multi-modal sensor node 5
    ├── node_x               # Inertial measurement unit data (.pickle)

Each data entry follows the format: [nodeID]_[modalityName]_[environmentID]_[userID]_[activityName]_[trialID]_[timestamp].[filetype].

5. Quick Start with Octonet Code

For more details on working with the dataset programmatically, refer to the original README in the OctoNet code repository on GitHub: https://github.com/aiot-lab/OctoNet.

6. Contact & Disclaimer

Contact: Xie Zhang, Chenshu Wu, Xuan Liu.

Disclaimer: This dataset is provided as is without warranties of any kind and is intended for research/educational purposes only. The creators assume no responsibility for any misuse or damages.