{rfName}
Ch

Indexed in

License and Use

Icono OpenAccess

Citations

17

Altmetrics

Analysis of institutional authors

Ortega JdCorresponding AuthorSalgado L.Author

Share

April 11, 2022
Publications
>
Article
Sí

Challenges of Large-Scale Multi-Camera Datasets for Driver Monitoring Systems

Publicated to: Sensors. 22 (7): 2554- - 2022-04-01 22(7), DOI: 10.3390/s22072554

Authors:

Ortega, Juan Diego; Canas, Paola Natalia; Nieto, Marcos; Otaegui, Oihana; Salgado, Luis
[+]

Affiliations

Univ Politecn Madrid UPM, ETS Ingn Telecomun, Madrid 28040, Spain - Author
Univ Politecn Madrid UPM, Informat Proc & Telecommun Ctr, Grp Tratamiento Imagenes, Madrid 28040, Spain - Author
Universidad Politécnica de Madrid - Author
VICOMTech - Author
VICOMTech , Universidad Politécnica de Madrid - Author
Vicomtech Fdn, Basque Res & Technol Alliance BRTA, San Sebastian 20009, Spain - Author
See more

Abstract

Tremendous advances in advanced driver assistance systems (ADAS) have been possible thanks to the emergence of deep neural networks (DNN) and Big Data (BD) technologies. Huge volumes of data can be managed and consumed as training material to create DNN models which feed functions such as lane keeping systems (LKS), automated emergency braking (AEB), lane change assistance (LCA), etc. In the ADAS/AD domain, these advances are only possible thanks to the creation and publication of large and complex datasets, which can be used by the scientific community to benchmark and leverage research and development activities. In particular, multi-modal datasets have the potential to feed DNN that fuse information from different sensors or input modalities, producing optimised models that exploit modality redundancy, correlation, complementariness and association. Creating such datasets pose a scientific and engineering challenge. The BD dimensions to cover are volume (large datasets), variety (wide range of scenarios and context), veracity (data labels are verified), visualization (data can be interpreted) and value (data is useful). In this paper, we explore the requirements and technical approach to build a multi-sensor, multi-modal dataset for video-based applications in the ADAS/AD domain. The Driver Monitoring Dataset (DMD) was created and partially released to foster research and development on driver monitoring systems (DMS), as it is a particular sub-case which receives less attention than exterior perception. Details on the preparation, construction, post-processing, labelling and publication of the dataset are presented in this paper, along with the announcement of a subsequent release of DMD material publicly available for the community.
[+]

Keywords

automotivedatasetsdriver monitoringmulti-cameravisionAccidents, trafficAdasAttentionAutomobile drivingAutomotiveDatasetsDriver monitoringHead poseMulti-cameraNeural networks, computer

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Sensors due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2022, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Analytical Chemistry.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-12-21:

  • Google Scholar: 4
  • WoS: 5
  • Scopus: 8
[+]

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-12-21:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 35.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 35 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 13.
  • The number of mentions on the social network X (formerly Twitter): 4 (Altmetric).
  • The number of mentions in news outlets: 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
[+]

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (ORTEGA VALDIVIESO, JUAN DIEGO) and Last Author (SALGADO ALVAREZ DE SOTOMAYOR, LUIS).

the author responsible for correspondence tasks has been ORTEGA VALDIVIESO, JUAN DIEGO.

[+]