<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this paper, we describe our team’s data processing practice for an event-based camera dataset. In addition to the event-based camera data, the Agri-EBV dataset contains data from LIDAR, RGB, depth cameras, temperature, moisture, and atmospheric pressure sensors. We describe data transfer from a platform, automatic and manual validation of data quality, conversions to multiple formats, and structuring of the final data. Accurate time offset estimation between sensors achieved in the dataset uses IMU data generated by purposeful movements of the sensor platform. Therefore, we also outline partitioning of the data and time alignment calculation during post-processing.</p>
</abstract>

In this paper, we describe our team’s data processing practice for an event-based camera dataset. In addition to the event-based camera data, the Agri-EBV dataset contains data from LIDAR, RGB, depth cameras, temperature, moisture, and atmospheric pressure sensors. We describe data transfer from a platform, automatic and manual validation of data quality, conversions to multiple formats, and structuring of the final data. Accurate time offset estimation between sensors achieved in the dataset uses IMU data generated by purposeful movements of the sensor platform. Therefore, we also outline partitioning of the data and time alignment calculation during post-processing.

The Process of Data Validation and Formatting for an Event-Based Vision Dataset in Agricultural Environments

Applied Computer Systems

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this paper, we describe our team’s data processing practice for an event-based camera dataset. In addition to the event-based camera data, the Agri-EBV...

The Process of Data Validation and Formatting for an Event-Based Vision Dataset in Agricultural Environments

Data publikacji: 30 gru 2021

Zakres stron: 173 - 177

DOI: https://doi.org/10.2478/acss-2021-0021

Słowa kluczowe
Dataset creation, event-based vision, neuromorphic vision dataset

© 2021 Maris Galauskis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Process of Data Validation and Formatting for an Event-Based Vision Dataset in Agricultural Environments

Data publikacji: 30 gru 2021

Zakres stron: 173 - 177

DOI: https://doi.org/10.2478/acss-2021-0021

Słowa kluczoweDataset creation, event-based vision, neuromorphic vision dataset

© 2021 Maris Galauskis et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Dataset creation, event-based vision, neuromorphic vision dataset