Fingerspelling recognition through classification of letter-to-letter transitions
Publication
, Journal Article
Ricco, S; Tomasi, C
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
December 29, 2010
We propose a new principle for recognizing .ngerspelling sequences from American Sign Language (ASL). Instead of training a system to recognize the static posture for each letter from an isolated frame, we recognize the dynamic gestures corresponding to transitions between letters. This eliminates the need for an explicit temporal segmentation step, which we show is error-prone at speeds used by native signers. We present results from our system recognizing 82 different words signed by a single signer, using more than an hour of training and test video. We demonstrate that recognizing letter-to-letter transitions without temporal segmentation is feasible and results in improved performance. © Springer-Verlag 2010.
Duke Scholars
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
December 29, 2010
Volume
5996 LNCS
Issue
PART 3
Start / End Page
214 / 225
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
Citation
APA
Chicago
ICMJE
MLA
NLM
Ricco, S., & Tomasi, C. (2010). Fingerspelling recognition through classification of letter-to-letter transitions. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5996 LNCS(PART 3), 214–225. https://doi.org/10.1007/978-3-642-12297-2_21
Ricco, S., and C. Tomasi. “Fingerspelling recognition through classification of letter-to-letter transitions.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5996 LNCS, no. PART 3 (December 29, 2010): 214–25. https://doi.org/10.1007/978-3-642-12297-2_21.
Ricco S, Tomasi C. Fingerspelling recognition through classification of letter-to-letter transitions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2010 Dec 29;5996 LNCS(PART 3):214–25.
Ricco, S., and C. Tomasi. “Fingerspelling recognition through classification of letter-to-letter transitions.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5996 LNCS, no. PART 3, Dec. 2010, pp. 214–25. Scopus, doi:10.1007/978-3-642-12297-2_21.
Ricco S, Tomasi C. Fingerspelling recognition through classification of letter-to-letter transitions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2010 Dec 29;5996 LNCS(PART 3):214–225.
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
December 29, 2010
Volume
5996 LNCS
Issue
PART 3
Start / End Page
214 / 225
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences