American Sign Language Image Dataset (ASLID)

Srujana Gattupalli, Amir Ghaderi
Vision-Learning-Mining Laborartory
The Universiy of Texas at Arlington, TX, USA


We present the American Sign Language Image Dataset (ASLID) with images extracted from Gallaudet Dictionary videos[1] and American Sign Language Lexicon Video Dataset(ASLLVD)[2] with annotations for upper body joint locations. The annotation file contains image video and frame name and 7 upper body joint co-ordinates, namely left hand, left elbow, left shoulder, head, right hand, right shoulder, right wrist. We also provide a tool to visualize the annotations. For the purpose of Upper body pose estimation experiments we have segregated the training and test set.

Training Images

Our training set comprises of 809 ASLID images(240 X 352) from different signs from six different native ASL signers from Gallaudet Dictionary videos[1] and annotations for them. We have not provided images here due to copyright issues and can be requested by emailing authors. The annotations tool to display annotations and tool to extract image given a video and frame number are provided in section below.

Test Images

The test set we have used 479 ASLID images (480 X 640) from two native ASL signers from ASLLVD videos[2]. Note:The frame numbers used in our annotations start from 1. The annotations shown in video frames start from 0.

Images can be downloaded from the following link: ASLID_Testset





Variation in range of training poses is shown in the ground truth scatter plot below:


Variation in range of test set poses is shown in the ground truth scatter plot below:


If you use our dataset for your research work, please Cite our Paper:
"Evaluation of Deep Learning based Pose Estimation for Sign Language", Srujana Gattupalli, Amir Ghaderi, Vassilis Athitsos, International Conference on PErvasive Technologies Related to Assistive Environments, PETRA, Corfu Island Greece, June 2016.


[1]C. Valli, editor. The Gallaudet Dictionary of American Sign Language. Gallaudet U. Press, Washington, DC, 2006.

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