A dataset of labelled objects on raw video sequences

We present an object labelled dataset called SFU-HW-Objects-v1, which contains object labels for a set of raw video sequences. The dataset can be useful for the cases where both object detection accuracy and video coding efficiency need to be evaluated on the same dataset. Object ground-truths for 1...

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Detalles Bibliográficos
Autores principales: Choi, Hyomin, Hosseini, Elahe, Ranjbar Alvar, Saeed, Cohen, Robert A., Bajić, Ivan V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797526/
https://www.ncbi.nlm.nih.gov/pubmed/33457477
http://dx.doi.org/10.1016/j.dib.2020.106701
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author Choi, Hyomin
Hosseini, Elahe
Ranjbar Alvar, Saeed
Cohen, Robert A.
Bajić, Ivan V.
author_facet Choi, Hyomin
Hosseini, Elahe
Ranjbar Alvar, Saeed
Cohen, Robert A.
Bajić, Ivan V.
author_sort Choi, Hyomin
collection PubMed
description We present an object labelled dataset called SFU-HW-Objects-v1, which contains object labels for a set of raw video sequences. The dataset can be useful for the cases where both object detection accuracy and video coding efficiency need to be evaluated on the same dataset. Object ground-truths for 18 of the High Efficiency Video Coding (HEVC) v1 Common Test Conditions (CTC) sequences have been labelled. The object categories used for the labeling are based on the Common Objects in Context (COCO) labels. A total of 21 object classes are found in test sequences, out of the 80 original COCO label classes. Brief descriptions of the labeling process and the structure of the dataset are presented.
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spelling pubmed-77975262021-01-15 A dataset of labelled objects on raw video sequences Choi, Hyomin Hosseini, Elahe Ranjbar Alvar, Saeed Cohen, Robert A. Bajić, Ivan V. Data Brief Data Article We present an object labelled dataset called SFU-HW-Objects-v1, which contains object labels for a set of raw video sequences. The dataset can be useful for the cases where both object detection accuracy and video coding efficiency need to be evaluated on the same dataset. Object ground-truths for 18 of the High Efficiency Video Coding (HEVC) v1 Common Test Conditions (CTC) sequences have been labelled. The object categories used for the labeling are based on the Common Objects in Context (COCO) labels. A total of 21 object classes are found in test sequences, out of the 80 original COCO label classes. Brief descriptions of the labeling process and the structure of the dataset are presented. Elsevier 2020-12-26 /pmc/articles/PMC7797526/ /pubmed/33457477 http://dx.doi.org/10.1016/j.dib.2020.106701 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Choi, Hyomin
Hosseini, Elahe
Ranjbar Alvar, Saeed
Cohen, Robert A.
Bajić, Ivan V.
A dataset of labelled objects on raw video sequences
title A dataset of labelled objects on raw video sequences
title_full A dataset of labelled objects on raw video sequences
title_fullStr A dataset of labelled objects on raw video sequences
title_full_unstemmed A dataset of labelled objects on raw video sequences
title_short A dataset of labelled objects on raw video sequences
title_sort dataset of labelled objects on raw video sequences
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797526/
https://www.ncbi.nlm.nih.gov/pubmed/33457477
http://dx.doi.org/10.1016/j.dib.2020.106701
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