One-Stage-TFS: Thai One-Stage Fingerspelling Dataset

Published: 16 September 2024| Version 1 | DOI: 10.17632/rknd3wbz42.1
Contributor:
olarik surinta

Description

The Thai One-Stage Fingerspelling (One-Stage-TFS) dataset is a comprehensive resource designed to advance research in hand gesture recognition, explicitly focusing on the recognition of Thai sign language. This dataset comprises 7,200 images capturing 15 one-stage consonant gestures performed by undergraduate students from Rajabhat Maha Sarakham University, Thailand. The contributors include both expert students from the Special Education Department with proficiency in Thai sign language and students from other departments without prior sign language experience. Images were collected between July and December 2021 using a DSLR camera, with contributors demonstrating hand gestures against both simple and complex backgrounds. The One-Stage-TFS dataset presents challenges in detecting and recognizing hand gestures, offering opportunities to develop novel end-to-end recognition frameworks. Researchers can utilize this dataset to explore deep learning methods for hand detection, followed by feature extraction and recognition using techniques like convolutional neural networks, transformers, and adaptive feature fusion networks. The dataset supports a wide range of applications in computer science, including deep learning, computer vision, and pattern recognition, thereby encouraging further innovation and exploration in these fields. Keywords: One-stage fingerspelling; Fingerspelling recognition; Hand detection; Hand gesture recognition; Deep learning; Computer vision Subject: Computer Science Specific subject area: Fingerspelling recognition is a crucial component of hand gesture recognition frameworks. The Thai One-Stage Fingerspelling Dataset includes images and annotated files that indicate the location of the hand within the images. This dataset is designed to support the detection of hand gestures and the recognition of fingerspelling. Additionally, it is relevant to various fields, including deep learning, computer vision, pattern recognition, and computer science applications. Type of data: Image (JPG format) and Raw (XML format) Data collection: The Thai One-Stage Fingerspelling (One-Stage-TFS) Dataset provides fingerspelling in the Thai language, focusing exclusively on one-stage consonants. The dataset was collected between July and December 2021 by undergraduate students at Rajabhat Maha Sarakham University, Thailand. The contributors included students from the Special Education Department with experience in Thai sign language and students from other departments without experience. Data source location: Institution: Rajabhat Maha Sarakham University Province: Mahasarakham Country: Thailand Related research article: S. Lata, O. Surinta, An end-to-end Thai fingerspelling recognition framework with deep convolutional neural networks, ICIC Express Letters 16 (2022) 529–536. https://doi.org/10.24507/icicel.16.05.5529

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Institutions

Mahasarakham University

Categories

Computer Science, Image Classification, Convolutional Neural Network, Deep Learning, Long Short-Term Memory Network

Funding

Mahasarakham University

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