Tracking benchmark databases for video-based sign language recognition

Authors:
Philippe Dreuw;Jens Forster;Hermann Ney
Affiliations:
Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Aachen, Germany;Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Aachen, Germany;Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Aachen, Germany
Venue:
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Year:
2010

Citing 16
Cited 1

Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video

IEEE Transactions on Pattern Analysis and Machine Intelligence
The visual analysis of human movement: a survey

Computer Vision and Image Understanding
A framework for recognizing the simultaneous aspects of American sign language

Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
ARGo: An Architecture for Sign Language Recognition and Interpretation

Proceedings of Gesture Workshop on Progress in Gestural Interaction
Lucas-Kanade 20 Years On: A Unifying Framework

International Journal of Computer Vision
Robust Real-Time Face Detection

International Journal of Computer Vision
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape-From-Silhouette Across Time Part I: Theory and Algorithms

International Journal of Computer Vision
Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning

IEEE Transactions on Pattern Analysis and Machine Intelligence
Australian sign language recognition

Machine Vision and Applications
Tracking Using Dynamic Programming for Appearance-Based Sign Language Recognition

FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Hidden Conditional Random Fields for Gesture Recognition

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Real Time Large Vocabulary Continuous Sign Language Recognition Based on OP/Viterbi Algorithm

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape

International Journal of Computer Vision
Eigenfaces for recognition

Journal of Cognitive Neuroscience
Large-Vocabulary Continuous Sign Language Recognition Based on Transition-Movement Models

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

ISOcat data categories for signed language resources

GW'11 Proceedings of the 9th international conference on Gesture and Sign Language in Human-Computer Interaction and Embodied Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

A survey of video databases that can be used within a continuous sign language recognition scenario to measure the performance of head and hand tracking algorithms either w.r.t. a tracking error rate or w.r.t. a word error rate criterion is presented in this work. Robust tracking algorithms are required as the signing hand frequently moves in front of the face, may temporarily disappear, or cross the other hand. Only few studies consider the recognition of continuous sign language, and usually special devices such as colored gloves or blue-boxing environments are used to accurately track the regions-of-interest in sign language processing. Ground-truth labels for hand and head positions have been annotated for more than 30k frames in several publicly available video databases of different degrees of difficulty, and preliminary tracking results are presented.