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

2021
Māris Galauskis, Artūrs Ardavs

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.

Keywords
Dataset creation | Event-based vision | Neuromorphic vision dataset.
DOI
10.2478/acss-2021-0021
Hyperlink
https://sciendo.com/article/10.2478/acss-2021-0021

Galauskis, M., Ardavs, A. The Process of Data Validation and Formatting for an Event-Based Vision Dataset in Agricultural Environments. Applied Computer Systems, 2021, Vol. 26, No. 2, pp. 173-177. ISSN 2255-8683. e-ISSN 2255-8691. Available from: doi:10.2478/acss-2021-0021

Publication language
English (en)