MultiSensor-Home-2

MultiSensor-Home2.zip

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README.md

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----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+---
+
+A simple way to download the dataset:
+```
+# Make sure hf CLI is installed: pip install -U "huggingface_hub[cli]"
+hf download thanhhff/MultiSensor-Home2 --repo-type=dataset --local-dir dataset 
+```
+
+# MultiSensor-Home2: Benchmark for Multi-modal Multi-view Action Recognition in Home Environments
+
+MultiSensor-Home2 is an extended version of MultiSensor-Home1, captured in a different home layout while maintaining the same structure and recording settings.
+This dataset is designed for multi-view action recognition and transformer-based sensor fusion research.
+
+
+## 📊 Dataset Overview
+
+MultiSensor-Home is a comprehensive multi-view action recognition dataset captured in a real home environment. 
+The dataset features:
+
+- **Multi-view Setup**: 5 synchronized camera views (View1-View5)
+- **High-resolution**: Original resolution 4000×3000 pixels (available upon request)
+- **Optimized for Deep Learning**: Resized to 320×240 pixels for efficient training
+- **Temporal Annotations**: Precise start/end timestamps for each action
+- **Real-world Scenarios**: Natural human activities in home environment
+- **Action Classes**: 16 different action classes in this environment
+
+**Note**: The original high-resolution dataset (4000×3000 pixels) is available upon request. Please contact: nguyent [at] cs.is.i.nagoya-u.ac.jp
+
+## 🏠 Room Layout and Camera Setup
+
+![Home1 Layout](Home2-Layout.png)
+
+*Home1 floor plan showing camera positions and room layout*
+
+- **Room Layout**: Complete floor plan of the home environment
+- **Camera Positions**: Exact placement of all 5 cameras (View1-View5)
+- **Camera Orientations**: Direction and field of view for each camera
+- **Room Dimensions**: Spatial measurements and room configurations
+- **Recording Environment**: Overview of the home setup used for data collection
+
+This layout file is essential for understanding the spatial relationships between different camera views and the overall recording environment.
+
+
+## 🏠 Dataset Structure
+
+```
+MultiSensor-Home2/
+├── 01/                    # Recording session 1
+├── 02/                    # Recording session 2
+├── 03/                    # Recording session 3
+├── 04/                    # Recording session 4
+├── 05/                    # Recording session 5
+├── 06/                    # Recording session 6
+├── 07/                    # Recording session 7
+├── 08/                    # Recording session 8
+├── 09/                    # Recording session 9
+├── all_labels.json        # Complete annotations
+├── train_data.json        # Training split annotations
+├── test_data.json         # Test split annotations
+└── README.md              # This file
+```
+
+## 📹 Video File Naming Convention
+
+Videos follow the pattern: `{id}-{View}{number}-Part{part}.mp4`
+
+**Examples:**
+- `00-View1-Part1.mp4` - ID 00, View 1, Part 1
+- `15-View3-Part2.mp4` - ID 15, View 3, Part 2
+- `23-View5-Part1.mp4` - ID 23, View 5, Part 1
+
+## 🏷️ Action Classes
+
+The dataset contains **16 action classes** covering various human activities in the home environment:
+
+- **Basic Movements**: Sitdown, Standup, Enter, Exit
+- **Device Usage**: UseLaptop, UsePhone, ReadBook
+- **Environmental Control**: TurnOnLamp, TurnOffLamp
+- **Home Activities**: OpenCurtain, CloseCurtain, Eat, Drink
+- **And more...**
+
+## 📋 Annotation Format
+
+Each video segment is annotated with:
+
+```json
+{
+  "video_url_1": "01/00-View1-Part1.mp4",
+  "video_url_2": "01/00-View2-Part1.mp4",
+  "video_url_3": "01/00-View3-Part1.mp4",
+  "video_url_4": "01/00-View4-Part1.mp4",
+  "video_url_5": "01/00-View5-Part1.mp4",
+  "tricks": [
+    {
+      "start": 0.6758380883417825,
+      "end": 6.314058810132165,
+      "channel": 0,
+      "labels": [
+        "Enter"
+      ]
+    }
+}
+```
+
+### Annotation Fields:
+- **video_url_1-5**: Paths to the 5 synchronized video views
+- **start/end**: Temporal boundaries in seconds
+- **labels**: Action label for the time segment
+
+
+## 📧 Original High-Resolution Dataset
+
+The original dataset at full resolution (4000×3000 pixels) is available upon request.
+
+Please include:
+- Your name and affiliation
+- Intended use of the dataset
+- Brief description of your research
+
+## 📄 License and Citation
+
+When using this dataset, please cite our paper:
+
+```bibtex
+@inproceedings{nguyen2025multisensor,
+  author    = {Trung Thanh Nguyen and Yasutomo Kawanishi and Vijay John and Takahiro Komamizu and Ichiro Ide},
+  title     = {MultiSensor-Home: A Wide-area Multi-modal Multi-view Dataset for Action Recognition and Transformer-based Sensor Fusion},
+  booktitle = {Proceedings of the 19th IEEE International Conference on Automatic Face and Gesture Recognition},
+  year      = {2025},
+  note      = {Best Student Paper Award}
+}
+```
+
+## 🤝 Contributing
+
+We welcome contributions and feedback. If you find any issues or have suggestions for improvements, please contact us.
+
+## 📞 Contact
+
+For questions about the dataset, paper, or to request the original high-resolution version:
+
+**Email**: nguyent [at] cs.is.i.nagoya-u.ac.jp
+
+## Acknowledgement
+This work was partly supported by Japan Society for the Promotion of Science (JSPS) KAKENHI JP21H03519 and JP24H00733.
+
+---
+
+*This dataset is designed to advance research in multi-view action recognition, sensor fusion, and transformer-based approaches for understanding human activities in real-world environments.*