Data Formats

This dataset is for paper “Domain-Agnostic Sample-Effcient Wireless Indoor Crowd Counting via Few-shot Learning”, which has been submitted for potential journal publication. The conference version is available in IEEE WOCC 2022 . The dataset contains 9 “pickle” file in total. Each file contains split CSI amplitude data, phase difference data and labels. Data collection scenarios are shown as follows:

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Each scenario contains three crowd motion types data: Static, Dynamic and Mixed.
Static: volunteers are required to remain seated but can act freely, such as eating, typing, or sleeping;
Dynamic: volunteers walk randomly walk around the venue;
Mixed: there is no restriction to the volunteers’ activities, and they can move freely in the venue including but not limited to walking, sitting, eating, and sleeping.

Each type data contains a crowd range of 0-8 people. And each class contains 600 samples.

Data Links

Usage in Python

import pickle
import numpy
with open(“office_los_static.pickle”, “rb”) as file:
        dataset = pickle.load(file)
        csi_amp = dataset[“abs”]
        csi_pha = dataset[“phase_df”]
        csi_label = dataset[“labels”]

“abs”: original amplitude data from split CSI stream.
“phase_df”: phase difference data, by computing difference between two adjacent receiving antennas.
“labels”: label of data, is the same as the number of people in the scene.