Attribute annotation and bias evaluation in visual datasets for autonomous driving
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- dc.contributor.author Fernández Llorca, David
- dc.contributor.author Frau Amar, Pedro
- dc.contributor.author Parra, Ignacio
- dc.contributor.author Izquierdo, Rubén
- dc.contributor.author Gómez Gutiérrez, Emilia, 1975-
- dc.date.accessioned 2025-11-10T06:43:21Z
- dc.date.available 2025-11-10T06:43:21Z
- dc.date.issued 2024
- dc.description.abstract This paper addresses the often overlooked issue of fairness in the autonomous driving domain, particularly in vision-based perception and prediction systems, which play a pivotal role in the overall functioning of Autonomous Vehicles (AVs). We focus our analysis on biases present in some of the most commonly used visual datasets for training person and vehicle detection systems. We introduce an annotation methodology and a specialised annotation tool, both designed to annotate protected attributes of agents in visual datasets. We validate our methodology through an inter-rater agreement analysis and provide the distribution of attributes across all datasets. These include annotations for the attributes age, sex, skin tone, group, and means of transport for more than 90K people, as well as vehicle type, colour, and car type for over 50K vehicles. Generally, diversity is very low for most attributes, with some groups, such as children, wheelchair users, or personal mobility vehicle users, being extremely underrepresented in the analysed datasets. The study contributes significantly to efforts to consider fairness in the evaluation of perception and prediction systems for AVs. This paper follows reproducibility principles. The annotation tool, scripts and the annotated attributes can be accessed publicly at https://github.com/ec-jrc/humaint_annotator.en
- dc.description.sponsorship This work was mainly funded by the HUMAINT project by the Directorate-General Joint Research Centre of the European Commission. It was also partially funded by Research Grants PID2020-114924RB-I00 and PDC2021-121324-I00 (Spanish Ministry of Science and Innovation).en
- dc.format.mimetype application/pdf
- dc.identifier.citation Fernández Llorca D, Frau P, Parra I, Izquierdo R, Gómez E. Attribute annotation and bias evaluation in visual datasets for autonomous driving. J Big Data. 2024 Sep 27;11(1):137. DOI: 10.1186/s40537-024-00976-9
- dc.identifier.doi http://dx.doi.org/10.1186/s40537-024-00976-9
- dc.identifier.issn 2196-1115
- dc.identifier.uri http://hdl.handle.net/10230/71822
- dc.language.iso eng
- dc.publisher Springer
- dc.relation.ispartof Journal of Big Data. 2024 Sep 27;11(1):137
- dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-114924RB-I00
- dc.rights © European Union 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
- dc.subject.keyword Autonomous drivingen
- dc.subject.keyword Computer visionen
- dc.subject.keyword Biasen
- dc.subject.keyword Fairnessen
- dc.subject.keyword Annotationen
- dc.subject.keyword Attributesen
- dc.subject.keyword Personsen
- dc.subject.keyword Vehiclesen
- dc.title Attribute annotation and bias evaluation in visual datasets for autonomous drivingen
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion