Dataset of manually classified images obtained from a construction site

Alexandre Almeida Del Savio; FELICITA LUNA TORRES ANA; Daniel Cardenas; Mónica Vergara; Gianella Urday Ibarra

doi:10.1016/j.dib.2022.108042

Dataset of manually classified images obtained from a construction site

Alexandre Almeida Del Savio
, FELICITA LUNA TORRES ANA
, Daniel Cardenas
, Mónica Vergara
, Gianella Urday Ibarra

Producción científica: Contribución a una revista › Artículo (Contribución a Revista) › revisión exhaustiva

9 Citas (Scopus)

Resumen

A manually classified dataset of images obtained by four static cameras located around a construction site is presented. Eight object classes, typically found in a construction environment, were considered. The dataset consists of 1046 images selected from video footage by a frame extraction algorithm and txt files containing the objects' class and coordinates information. These data can be used to develop computer vision techniques in the engineering and construction fields.

Idioma original	Inglés
Número de artículo	108042
Publicación	Data in Brief
Volumen	42
DOI	https://doi.org/10.1016/j.dib.2022.108042 https://doi.org/10.1016/j.dib.2022.108042
Estado	Publicada - jun. 2022

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10.1016/j.dib.2022.108042Licencia: CC BY
10.1016/j.dib.2022.108042

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Inteligencia artificial aplicada al seguimiento, control y monitoreo de obras
Luna Torres, A. F. (Investigador adjunto), Almeida Del Savio, A. (Investigador principal), Cardenas Salas, D. E. (Investigador adjunto) & Vergara Olivera, M. A. (Asistente / Jefe de prácticas)
1/04/20 → 15/03/21
Proyecto: Investigación

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abstract = "A manually classified dataset of images obtained by four static cameras located around a construction site is presented. Eight object classes, typically found in a construction environment, were considered. The dataset consists of 1046 images selected from video footage by a frame extraction algorithm and txt files containing the objects' class and coordinates information. These data can be used to develop computer vision techniques in the engineering and construction fields.",

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AU - Savio, Alexandre Almeida Del

AU - ANA, FELICITA LUNA TORRES

AU - Cardenas, Daniel

AU - Vergara, Mónica

AU - Ibarra, Gianella Urday

N1 - Funding Information: The authors wish to thank Universidad de Lima for the use of equipment and image acquisition. This work was supported and funded by the Institute of Scientific Research of the University of Lima (IDIC) with Project Number PI.71.002.2020. Publisher Copyright: © 2022

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N2 - A manually classified dataset of images obtained by four static cameras located around a construction site is presented. Eight object classes, typically found in a construction environment, were considered. The dataset consists of 1046 images selected from video footage by a frame extraction algorithm and txt files containing the objects' class and coordinates information. These data can be used to develop computer vision techniques in the engineering and construction fields.

AB - A manually classified dataset of images obtained by four static cameras located around a construction site is presented. Eight object classes, typically found in a construction environment, were considered. The dataset consists of 1046 images selected from video footage by a frame extraction algorithm and txt files containing the objects' class and coordinates information. These data can be used to develop computer vision techniques in the engineering and construction fields.

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UR - https://www.scopus.com/pages/publications/85126605198

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M3 - Artículo (Contribución a Revista)

SN - 2352-3409

VL - 42

JO - Data in Brief

JF - Data in Brief

M1 - 108042

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Dataset of manually classified images obtained from a construction site

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