Search Results for author: Carol Neidle

Found 13 papers, 1 papers with code

Resources for Computer-Based Sign Recognition from Video, and the Criticality of Consistency of Gloss Labeling across Multiple Large ASL Video Corpora

no code implementations SignLang (LREC) 2022 Carol Neidle, Augustine Opoku, Carey Ballard, Konstantinos M. Dafnis, Evgenia Chroni, Dimitri Metaxas

The WLASL purports to be “the largest video dataset for Word-Level American Sign Language (ASL) recognition.” It brings together various publicly shared video collections that could be quite valuable for sign recognition research, and it has been used extensively for such research.

Sign Language Video Anonymization

no code implementations SignLang (LREC) 2022 Zhaoyang Xia, Yuxiao Chen, Qilong Zhangli, Matt Huenerfauth, Carol Neidle, Dimitri Metaxas

We modify a motion-based image animation model to generate high-resolution videos with the signer identity changed, but with the preservation of linguistically significant motions and facial expressions.

Image Animation Optical Flow Estimation

Bidirectional Skeleton-Based Isolated Sign Recognition using Graph Convolutional Networks

no code implementations LREC 2022 Konstantinos M. Dafnis, Evgenia Chroni, Carol Neidle, Dimitri Metaxas

To improve computer-based recognition from video of isolated signs from American Sign Language (ASL), we propose a new skeleton-based method that involves explicit detection of the start and end frames of signs, trained on the ASLLVD dataset; it uses linguistically relevant parameters based on the skeleton input.

Isolated Sign Recognition using ASL Datasets with Consistent Text-based Gloss Labeling and Curriculum Learning

no code implementations SLTAT (LREC) 2022 Konstantinos M. Dafnis, Evgenia Chroni, Carol Neidle, Dimitri Metaxas

We present a new approach for isolated sign recognition, which combines a spatial-temporal Graph Convolution Network (GCN) architecture for modeling human skeleton keypoints with late fusion of both the forward and backward video streams, and we explore the use of curriculum learning.

DiffSLVA: Harnessing Diffusion Models for Sign Language Video Anonymization

1 code implementation27 Nov 2023 Zhaoyang Xia, Carol Neidle, Dimitris N. Metaxas

While signers have expressed interest, for a variety of applications, in sign language video anonymization that would effectively preserve linguistic content, attempts to develop such technology have had limited success, given the complexity of hand movements and facial expressions.

Edge Detection Pose Estimation

Challenges for Linguistically-Driven Computer-Based Sign Recognition from Continuous Signing for American Sign Language

no code implementations1 Nov 2023 Carol Neidle

There have been recent advances in computer-based recognition of isolated, citation-form signs from video.

ASL Video Corpora & Sign Bank: Resources Available through the American Sign Language Linguistic Research Project (ASLLRP)

no code implementations19 Jan 2022 Carol Neidle, Augustine Opoku, Dimitris Metaxas

These data have been used for many types of research in linguistics and in computer-based sign language recognition from video; examples of such research are provided in the latter part of this article.

Sign Language Recognition

Detection of Major ASL Sign Types in Continuous Signing For ASL Recognition

no code implementations LREC 2016 Polina Yanovich, Carol Neidle, Dimitris Metaxas

In American Sign Language (ASL) as well as other signed languages, different classes of signs (e. g., lexical signs, fingerspelled signs, and classifier constructions) have different internal structural properties.

Multiple Instance Learning

A New Framework for Sign Language Recognition based on 3D Handshape Identification and Linguistic Modeling

no code implementations LREC 2014 Mark Dilsizian, Polina Yanovich, Shu Wang, Carol Neidle, Dimitris Metaxas

Current approaches to sign recognition by computer generally have at least some of the following limitations: they rely on laboratory conditions for sign production, are limited to a small vocabulary, rely on 2D modeling (and therefore cannot deal with occlusions and off-plane rotations), and/or achieve limited success.

3D Reconstruction Sign Language Recognition +1

Detecting Reduplication in Videos of American Sign Language

no code implementations LREC 2012 Zoya Gavrilov, Stan Sclaroff, Carol Neidle, Sven Dickinson

A framework is proposed for the detection of reduplication in digital videos of American Sign Language (ASL).

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