BD Sports-10: A comprehensive video dataset for Bangladeshi sports classification and analysis

Bangladesh has diverse and vibrant cultural sports, some of which have gained international recognition in recent years. However, there is a lack of standardized datasets for deep learning and computer vision tasks. To address this gap, BD Sports-10 was developed as a comprehensive dataset for Bangladeshi sports. It consists of ten unique sports categories, with a total of 3000 videos, 300 per class, with a resolution of 1920×1080 pixels and 30 frames per second (FPS). Each sport in the dataset features distinct rules, viewing angles, playground setups, and actions, which also depend on players' skills. The dataset captures a diverse range of actions, including jumping, running, tagging, throwing, attempting to hit a clay pot, and capturing an opponent before they cross a designated line. BD Sports-10 includes ten traditional and culturally significant sports: <i>Kabaddi, Nouka Baich, Lathi Khela, Kho Kho, Kanamachi, Toilakto Kolagach Arohon (Kolagach), Hari Vanga, Morog Lorai, Lathim,</i> and <i>Joldanga</i>. This standardized and balanced dataset is not only suitable for classification tasks but also for object detection, player tracking, and automated scoring systems. The dataset supports research in deep learning, machine learning, and computer vision by providing ready-to-use scripts, datasets, and preprocessing pipelines that facilitate diverse AI-based experimental workflows.

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Publication Details

Journal
Data in Brief
Published
2026-01-05
DOI
https://doi.org/10.1016/j.dib.2025.112442
Primary Topic
Human Pose and Action Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

BD Sports-10: A comprehensive video dataset for Bangladeshi sports classification and analysis

Shifatun Nur Shifa, Niloy Barua Supta, Khondaker A. Mamun, Wazih Ullah Tanzim
Data in Brief
Human Pose and Action Recognition
article

BD Sports-10: A comprehensive video dataset for Bangladeshi sports classification and analysis

Shifatun Nur Shifa, Niloy Barua Supta, Khondaker A. Mamun, Wazih Ullah Tanzim
article en

Abstract

Bangladesh has diverse and vibrant cultural sports, some of which have gained international recognition in recent years. However, there is a lack of standardized datasets for deep learning and computer vision tasks. To address this gap, BD Sports-10 was developed as a comprehensive dataset for Bangladeshi sports. It consists of ten unique sports categories, with a total of 3000 videos, 300 per class, with a resolution of 1920×1080 pixels and 30 frames per second (FPS). Each sport in the dataset features distinct rules, viewing angles, playground setups, and actions, which also depend on players' skills. The dataset captures a diverse range of actions, including jumping, running, tagging, throwing, attempting to hit a clay pot, and capturing an opponent before they cross a designated line. BD Sports-10 includes ten traditional and culturally significant sports: <i>Kabaddi, Nouka Baich, Lathi Khela, Kho Kho, Kanamachi, Toilakto Kolagach Arohon (Kolagach), Hari Vanga, Morog Lorai, Lathim,</i> and <i>Joldanga</i>. This standardized and balanced dataset is not only suitable for classification tasks but also for object detection, player tracking, and automated scoring systems. The dataset supports research in deep learning, machine learning, and computer vision by providing ready-to-use scripts, datasets, and preprocessing pipelines that facilitate diverse AI-based experimental workflows.

Data in BriefVol. 65
United International University (BD), Premier University (BD)
Openalex Percentile: Top 98%
Human Pose and Action Recognition
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