Updating a dataset of labelled objects on raw video sequences with unique object IDs()

We present an update to the previously published dataset known as SFU-HW-Objects-v1. The new dataset is called SFU-HW-Tracks-v1 and contains object annotations with unique object identities (IDs) for the High Efficiency Video Coding (HEVC) v1 Common Test Conditions (CTC) sequences. For each video fr...

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Detalles Bibliográficos
Autores principales: Tanaka, Takehiro, Choi, Hyomin, Bajić, Ivan V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841997/
https://www.ncbi.nlm.nih.gov/pubmed/35198673
http://dx.doi.org/10.1016/j.dib.2022.107892
Descripción
Sumario:We present an update to the previously published dataset known as SFU-HW-Objects-v1. The new dataset is called SFU-HW-Tracks-v1 and contains object annotations with unique object identities (IDs) for the High Efficiency Video Coding (HEVC) v1 Common Test Conditions (CTC) sequences. For each video frame, ground truth annotations include object class ID, object ID, and bounding box location and its dimensions. The dataset can be used to evaluate object tracking performance on uncompressed video sequences and study the relationship between video compression and object tracking, which was not possible using SFU-HW-Objects-v1.

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