Lobo-Neto Vicente Coelho, Pedrini Helio
Institute of Computing, University of Campinas, Av. Albert Einstein 1251, Campinas, SP 13083-852, Brazil.
Data Brief. 2024 Jul 31;56:110780. doi: 10.1016/j.dib.2024.110780. eCollection 2024 Oct.
This paper presents Libras SignWriting Handshape (LSWH100), a new handshape dataset focused on Sign Language Recognition. The dataset includes 144,000 synthetic images of a realistic human hand, covering 100 distinct handshape classes used in Brazilian Sign Language (Libras). Handshapes are named using the convention from SignWriting, a writing system for sign languages. The dataset contains annotations for classification, detection, segmentation, depth estimation, and 3D hand keypoints. Images include indoor and outdoor scenes during different times of day, centered on a single hand that can change size, 3D rotation, and skin tone. We generated these images using Blender, a free and open-source 3D creation software. This is a challenging dataset that can be further explored. With a focus on sign language, this dataset has the potential to advance sign language recognition systems, positively impacting those who rely on sign language for communication.
本文介绍了天秤座手语手型（LSWH100），这是一个专注于手语识别的新手型数据集。该数据集包含144,000张逼真的人类手部合成图像，涵盖巴西手语（Libras）中使用的100个不同手型类别。手型按照手语书写系统SignWriting的惯例命名。该数据集包含用于分类、检测、分割、深度估计和3D手部关键点的注释。图像包括一天中不同时间的室内和室外场景，以一只可以改变大小、3D旋转和肤色的手为中心。我们使用免费开源的3D创作软件Blender生成了这些图像。这是一个具有挑战性的数据集，可以进一步探索。以手语为重点，该数据集有潜力推进手语识别系统，对依靠手语进行交流的人产生积极影响。
