MIUN dataset for semi-autonomous powered wheelchair control

SND-ID: 2021-303

Description Data and documentation

Alternative title

MIUN-Feet dataset

Creator/Principal investigator(s)

Cristian Vilar - Mid Sweden University

Description

A powered wheelchair detects and follows a caregiver walking beside it. Caregiver recognition is performed by detecting the caregiver feet above the floor. The dataset contains a set of images and annotated labels for a feet recognition application. The camera is placed in the right armrest of the powered wheelchair, tilted down 45 degrees. The camera measures the caregiver's feet walking beside the powered wheelchair. The dataset also includes the training, validation and test files definition for different camera image outputs (Depth, RGB, RGB-D), scenarios and light conditions.

Language

English

Research principal, contributors, and funding
Protection and ethical review

Data contains personal data

No

Method

Sampling procedure

The camera is placed in the right armrest of the powered wheelchair, tilted down 45 degrees. The camera measures the caregiver's feet walking beside the powered wheelchair. The dataset also includes the training, validation and test files definition for different camera image outputs (Depth, RGB, RGB-D), scenarios and light conditions.
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Publications


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Dataset
MIUN dataset for semi-autonomous powered wheelchair control

Download data

readme.txt (1.79 KB)
Data_D.zip (305.88 MB)
Data_RGBD.zip (4.52 GB)
Train_Test.zip (96.13 KB)

Description

Images are captured by an Intel Realsense D455 depth camera. The dataset includes separate image files for each camera output (Depth, RGB, RGBD) and annotated labels for each frame. Each camera measurement contains 30 seconds of images, recorded at 6 frames/second (180 frames). The total number of images is 6000 (3000 including feet labels and 3000 without). The labelling process has been performed using the software labelImg. Sample scenarios and related frame numbers are defined in the readme.

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Version 1

Citation

Cristian Vilar. Mid Sweden University, Department Electronic design (2021). <em>MIUN dataset for semi-autonomous powered wheelchair control</em>. Swedish National Data Service. Version 1. <a href="https://doi.org/10.5878/k44d-3y06">https://doi.org/10.5878/k44d-3y06</a>

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Data format / data structure

Text

Still image

Creator/Principal investigator(s)

Cristian Vilar - Mid Sweden University

Contact for questions about the data

Published: 2021-11-16