21.4.3.3.2 Sign Language, Fingerspelling

Chapter Contents (Back)
Finger Spelling. ASL. Sign Language.

Bowden, R.[Richard], Sarhadi, M.[Mansoor],
A non-linear model of shape and motion for tracking finger spelt American sign language,
IVC(20), No. 9-10, August 2002, pp. 597-607.
WWW Link. 0208
BibRef
Earlier:
Building Temporal Models for Gesture Recognition,
BMVC00(xx-yy).
PDF File. 0009
BibRef

Tsechpenakis, G.[Gabriel], Metaxas, D.N.[Dimitris N.], Neidle, C.[Carol],
Learning-based dynamic coupling of discrete and continuous trackers,
CVIU(103), No. 2-3, November-December 2006, pp. 140-156.
WWW Link. 0611
Model-based continuous tracking; Appearance-based discrete tracking; Coupling trackers; Data-driven tracking error; 3D hand tracking; Fingerspelling segmentation BibRef

Michael, N.[Nicholas], Yang, P.[Peng], Liu, Q.S.[Qing-Shan], Metaxas, D.N.[Dimitris N.], Neidle, C.[Carol],
A Framework for the Recognition of Nonmanual Markers in Segmented Sequences of American Sign Language,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Yang, H.D.[Hee-Deok], Sclaroff, S.[Stan], Lee, S.W.[Seong-Whan],
Sign Language Spotting with a Threshold Model Based on Conditional Random Fields,
PAMI(31), No. 7, July 2009, pp. 1264-1277.
IEEE DOI 0905
Signs appear in a continuous stream with other gestures. BibRef

Yang, H.D.[Hee-Deok], Lee, S.W.[Seong-Whan],
Simultaneous spotting of signs and fingerspellings based on hierarchical conditional random fields and boostmap embeddings,
PR(43), No. 8, August 2010, pp. 2858-2870.
Elsevier DOI 1006
Sign language spotting; Fingerspelling spotting; Conditional random field See also Sign Language Spotting with a Threshold Model Based on Conditional Random Fields. BibRef

Yang, H.D.[Hee-Deok], Lee, S.W.[Seong-Whan],
Robust sign language recognition by combining manual and non-manual features based on conditional random field and support vector machine,
PRL(34), No. 16, 2013, pp. 2051-2056.
Elsevier DOI 1310
BibRef
Earlier:
Robust Sign Language Recognition with Hierarchical Conditional Random Fields,
ICPR10(2202-2205).
IEEE DOI 1008
Sign language recognition BibRef

Cho, S.S.[Seong-Sik], Yang, H.D.[Hee-Deok], Lee, S.W.[Seong-Whan],
Sign language spotting based on semi-Markov Conditional Random Field,
WACV09(1-6).
IEEE DOI 0912
BibRef

Ishida, H.[Hiroyuki], Takahashi, T.[Tomokazu], Ide, I.[Ichiro], Murase, H.[Hiroshi],
A Hilbert warping method for handwriting gesture recognition,
PR(43), No. 8, August 2010, pp. 2799-2806.
Elsevier DOI 1006
BibRef
Earlier:
A Hilbert warping method for camera-based finger-writing recognition,
ICPR08(1-5).
IEEE DOI 0812
Sequence alignment; Classification method; Analytic signal; Gesture recognition BibRef

Suraj, M.G., Guru, D.S., Manjunath, S.,
Recognition Of Postal Codes From Fingerspelling Video Sequence,
IJIG(11), No. 1, January 2011, pp. 21-41.
DOI Link 1103
BibRef

Altun, O.[Oguz], Albayrak, S.[Songül],
Turkish fingerspelling recognition system using Generalized Hough Transform, interest regions, and local descriptors,
PRL(32), No. 13, 1 October 2011, pp. 1626-1632.
Elsevier DOI 1109
BibRef
Earlier:
Increasing the Effect of Fingers in Fingerspelling Hand Shapes by Thick Edge Detection and Correlation with Penalization,
PSIVT06(1133-1141).
Springer DOI 0612
Generalized Hough Transform; DoG; SIFT; Interest regions; Local descriptors; Fingerspelling recognition BibRef

Dahmani, D.[Djamila], Larabi, S.[Slimane],
User-independent system for sign language finger spelling recognition,
JVCIR(25), No. 5, 2014, pp. 1240-1250.
Elsevier DOI 1406
Hand posture BibRef

Kane, L.[Lalit], Khanna, P.[Pritee],
A framework for live and cross platform fingerspelling recognition using modified shape matrix variants on depth silhouettes,
CVIU(141), No. 1, 2015, pp. 138-151.
Elsevier DOI 1512
Depth sensing BibRef

Pattanaworapan, K.[Kanjana], Chamnongthai, K.[Kosin], Guo, J.M.[Jing-Ming],
Signer-independence finger alphabet recognition using discrete wavelet transform and area level run lengths,
JVCIR(38), No. 1, 2016, pp. 658-677.
Elsevier DOI 1605
Sign language recognition BibRef

Chang, H.J.[Hyung Jin], Garcia-Hernando, G.[Guillermo], Tang, D.H.[Dan-Hang], Kim, T.K.[Tae-Kyun],
Spatio-Temporal Hough Forest for efficient detection-localisation-recognition of fingerwriting in egocentric camera,
CVIU(148), No. 1, 2016, pp. 87-96.
Elsevier DOI 1606
Spatio-Temporal Hough forest BibRef

Chen, M., Al Regib, G., Juang, B.H.,
Feature Processing and Modeling for 6D Motion Gesture Recognition,
MultMed(15), No. 3, 2013, pp. 561-571.
IEEE DOI 1303
BibRef

Chen, M., Al Regib, G., Juang, B.H.,
Air-Writing Recognition Part I: Modeling and Recognition of Characters, Words, and Connecting Motions,
HMS(46), No. 3, June 2016, pp. 403-413.
IEEE DOI 1605
BibRef
And:
Air-Writing Recognition Part II: Detection and Recognition of Writing Activity in Continuous Stream of Motion Data,
HMS(46), No. 3, June 2016, pp. 436-444.
IEEE DOI 1605
Covariance matrices. Atmospheric modeling BibRef


Hosoe, H., Sako, S., Kwolek, B.,
Recognition of JSL finger spelling using convolutional neural networks,
MVA17(85-88)
DOI Link 1708
Assistive technology, Cameras, Gesture recognition, Solid modeling, Three-dimensional displays, Thumb BibRef

Artyukhin, S.G., Mestetskiy, L.M.,
Dactyl Alphabet Gesture Recognition in a Video Sequence Using Microsoft Kinect,
PTVSBB15(83-86).
DOI Link 1508
BibRef

Hameed, M.Z.[Muhammad Zaid], Garcia-Hernando, G.[Guillermo],
Novel spatio-temporal features for fingertip writing recognition in egocentric viewpoint,
MVA15(484-488)
IEEE DOI 1507
Cameras BibRef

Silva, S.[Samira], Schwartz, W.R.[William Robson], Cámara-Chávez, G.[Guillermo],
Spatial Pyramid Matching for Finger Spelling Recognition in Intensity Images,
CIARP14(629-636).
Springer DOI 1411
BibRef

Rioux-Maldague, L.[Lucas], Giguere, P.[Philippe],
Sign Language Fingerspelling Classification from Depth and Color Images Using a Deep Belief Network,
CRV14(92-97)
IEEE DOI 1406
Accuracy BibRef

Weerasekera, C.S., Jaward, M.H., Kamrani, N.,
Robust ASL Fingerspelling Recognition Using Local Binary Patterns and Geometric Features,
DICTA13(1-8)
IEEE DOI 1402
computer vision BibRef

Kim, T.[Taehwan], Shakhnarovich, G.[Greg], Livescu, K.[Karen],
Fingerspelling Recognition with Semi-Markov Conditional Random Fields,
ICCV13(1521-1528)
IEEE DOI 1403
BibRef

Lahamy, H., Lichti, D.D.[Derek D.],
Robust Real-time And Rotation-invariant American Sign Language Alphabet Recognition Using Range Camera,
ISPRS12(XXXIX-B5:217-222).
DOI Link 1209
BibRef

Saldivar-Piñon, L.[Leonardo], Chacon-Murguia, M.I.[Mario I.], Sandoval-Rodriguez, R.[Rafael], Vega-Pineda, J.[Javier],
Human Sign Recognition for Robot Manipulation,
MCPR12(107-116).
Springer DOI 1208
BibRef

Rios Soria, D.J.[David J.], Schaeffer, S.E.[Satu Elisa],
A Tool for Hand-Sign Recognition,
MCPR12(137-146).
Springer DOI 1208
BibRef

Lilha, H.[Himanshu], Shivmurthy, D.[Devashish],
Evaluation of features for automated transcription of dual-handed sign language alphabets,
ICIIP11(1-5).
IEEE DOI 1112
BibRef

Pugeault, N.[Nicolas], Bowden, R.[Richard],
Spelling it out: Real-time ASL fingerspelling recognition,
ConDepth11(1114-1119).
IEEE DOI 1201
BibRef

Rashid, O.[Omer], Al-Hamadi, A.[Ayoub],
Utilizing the Bezier descriptors for hand gesture recognition,
ICIP15(3525-3529)
IEEE DOI 1512
Bezier Curves; Gesture Recognition; HMM BibRef

Rashid, O.[Omer], Al-Hamadi, A.[Ayoub], Michaelis, B.[Bernd],
Utilizing Invariant Descriptors for Finger Spelling American Sign Language Using SVM,
ISVC10(I: 253-263).
Springer DOI 1011
BibRef

Ricco, S.[Susanna], Tomasi, C.[Carlo],
Fingerspelling Recognition through Classification of Letter-to-Letter Transitions,
ACCV09(III: 214-225).
Springer DOI 0909
BibRef

Jin, L.W.[Lian-Wen], Yang, D.[Duanduan], Zhen, L.X.[Li-Xin], Huang, J.C.[Jian-Cheng],
A Novel Vision based Finger-writing Character Recognition System,
ICPR06(I: 1104-1107).
IEEE DOI 0609
BibRef

Chen, Z.W.[Zhi-Wei], Lin, Y.C.[Yu-Cheng], Chiang, C.C.[Cheng-Chin],
In this paper, an approach for deaf-people,
ICPR06(II: 104-107).
IEEE DOI 0609
Finger writing interface. BibRef

Goh, P., Holden, E.J.[Eun-Jung],
Dynamic Fingerspelling Recognition using Geometric and Motion Features,
ICIP06(2741-2744).
IEEE DOI 0610
See also Australian sign language recognition. BibRef

Feris, R.S.[Rogerio S.], Turk, M.A.[Matthew A.], Raskar, R.[Ramesh], Tan, K.[Karhan], Ohashi, G.[Gosuke],
Exploiting Depth Discontinuities for Vision-Based Fingerspelling Recognition,
RealTimeHCI04(155).
IEEE DOI 0502
BibRef

Birk, H.[Henrik], Moeslund, T.B.[Thomas B.], and Madsen, C.B.[Claus B.],
Real-Time Recognition of Hand Alphabet Gestures Using Principal Component Analysis,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Uras, C., Verri, A.,
Sign Language Recognition: an Application of the Theory of Size Functions,
BMVC95(xx-yy).
PDF File. 9509
BibRef
Earlier:
On the recognition of the alphabet of the sign language through size functions,
ICPR94(B:334-338).
IEEE DOI 9410
BibRef

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Biometrics, General Systems .


Last update:Nov 18, 2017 at 20:56:18