2 code implementations • ICCV 2019 • Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane, Diane Brentari, Greg Shakhnarovich, Karen Livescu
In this paper we focus on recognition of fingerspelling sequences in American Sign Language (ASL) videos collected in the wild, mainly from YouTube and Deaf social media.
no code implementations • 26 Oct 2018 • Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane, Jonathan Michaux, Diane Brentari, Greg Shakhnarovich, Karen Livescu
As the first attempt at fingerspelling recognition in the wild, this work is intended to serve as a baseline for future work on sign language recognition in realistic conditions.
no code implementations • 26 Sep 2016 • Taehwan Kim, Jonathan Keane, Weiran Wang, Hao Tang, Jason Riggle, Gregory Shakhnarovich, Diane Brentari, Karen Livescu
Recognizing fingerspelling is challenging for a number of reasons: It involves quick, small motions that are often highly coarticulated; it exhibits significant variation between signers; and there has been a dearth of continuous fingerspelling data collected.
no code implementations • LREC 2014 • Leah Geer, Jonathan Keane
Clips were modified in the following ways: all were slowed down to half speed, one-third of the clips were modified to black out the transition portion of the fingerspelling stream, and one-third modified to have holds blacked out.