American Sign Language Lexicon Video Dataset (ASLLVD)

This website describes our ongoing work at Boston University and the University of Texas at Arlington to develop a computer vision system that will identify a sign from video input for dictionary look-up. As part of that project, we are producing a large and expanding public dataset containing video sequences of thousands of distinct ASL signs (produced by native signers of ASL), along with annotations of those sequences, including start/end frames and class label (i.e., gloss-based identification) of every sign.

The data presented here have been collected as part of the NSF funded effort NSF0705749. This project is a collaboration among:

  • Stan Sclaroff, Professor of Computer Science, Boston University
  • Carol Neidle, Professor of French and Linguistics, Boston University
  • Vassilis Athitsos, Assistant Professor of Computer Science and Engineering, University of Texas, Arlington

If you use these data in published work, please cite the following paper discussing the current project:

V. Athitsos, C. Neidle, S. Sclaroff, J. Nash, A. Stefan, Q. Yuan and A. Thangali, The ASL Lexicon Video Dataset, CVPR 2008 Workshop on Human Communicative Behaviour Analysis (CVPR4HB'08) (pdf ps)

Datasets

Isolated sign videos

Videos of isolated signs from our capture sessions, with labels based on the glosses found in the Gallaudet Dictionary of American Sign Language, are available from the links below.

Lossless compressed videos are available for three views: front, side and face region. QuickTime format (with MPEG4 encoding) videos are available for the first few sessions and will be updated as gloss annotations are prepared.

The lossless compressed videos are about 1Gb each. If you wish to download a large number of these files, please contact us and we can determine a suitable way for data transfer to not overload the fileserver. A C++ library to read frames for this video format is available here.

  • QuickTime videos with sign gloss annotation

    sessions 1 & 2

  • Lossless compressed videos (videos are about 1Gb each)

    sessions 1 2 3 4 5 6

Test video sequences for isolated sign recognition

Video sequences used for testing performance of the isolated sign recognition system described in our CVPR4HB'08 paper are available from the links below.

  • QuickTime videos with sign gloss annotation

    test sessions 1 & 2

  • Lossless compressed videos (videos are about 1Gb each)

    test sessions 1 2

Related resources


Contacts

For questions regarding data capture and file formats:

athitsos AT uta.edu & sclaroff AT cs.bu.edu

For queries related to sign language and linguistic annotations:

carol AT bu.edu