3DO Dataset

3DO Dataset | On the Generalization of WiFi-based Person-centric Sensing in Through-Wall Scenarios

The 3DO dataset comprises 42 five-minute recordings (~1.25M WiFi packets) of three human activities performed by a single person, captured in a WiFi through-wall sensing scenario over three consecutive days. Each WiFi packet is annotated with a 3D trajectory label and a class label for the activities: walking (0), sitting (1), and lying (2).

The directories 3DO/d1/, 3DO/d2/, and 3DO/d3/ contain the sequences from days 1, 2, and 3, respectively. Furthermore, each sequence directory (e.g., 3DO/d1/w1/) contains a csiposreg.csv file storing the raw WiFi packet time series and a csiposreg_complex.npy cache file, which stores the complex Channel State Information (CSI) of the WiFi packet time series. (If missing, csiposreg_complex.npy is automatically generated by the provided dataloader.)

Dataset Structure:

/3DO

├── d1 <-- day 1 subdirectory

└── w1  <-- sequence subdirectory

└── csiposreg.csv <-- raw WiFi packet time series

└── csiposreg_complex.npy <-- CSI time series cache

├── d2 <-- day 2 subdirectory

├── d3 <-- day 3 subdirectory

Paper:

Strohmayer, J., Kampel, M. (2025). On the Generalization of WiFi-Based Person-Centric Sensing in Through-Wall Scenarios. In: Pattern Recognition. ICPR 2024. Lecture Notes in Computer Science, vol 15315. Springer, Cham. https://doi.org/10.1007/978-3-031-78354-8_13

BibTeX citation:

@inproceedings{strohmayerOn2025, author="Strohmayer, Julian and Kampel, Martin", title="On the Generalization of WiFi-Based Person-Centric Sensing in Through-Wall Scenarios", booktitle="Pattern Recognition", year="2025", publisher="Springer Nature Switzerland", address="Cham", pages="194--211", isbn="978-3-031-78354-8" }