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.
Elsevier DOI 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.
Elsevier DOI 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

Kane, L., Khanna, P.,
Vision-Based Mid-Air Unistroke Character Input Using Polar Signatures,
HMS(47), No. 6, December 2017, pp. 1077-1088.
IEEE DOI 1712
Gesture recognition, Heuristic algorithms, Hidden Markov models, Man-machine systems, Trajectory, Videos, Writing, Depth sensor, unistroke character input BibRef

Kim, P., Kim, K.S., Kim, S.,
Modified Nonnegative Matrix Factorization Using the Hadamard Product to Estimate Real-Time Continuous Finger-Motion Intentions,
HMS(47), No. 6, December 2017, pp. 1089-1099.
IEEE DOI 1712
Adaptation models, Data models, Estimation, Feature extraction, Fingers, Real-time systems, Robots, Finger-intention estimation, surface electromyogram (sEMG) BibRef

Li, R., Nguyen, M., Yan, W.Q.,
Morse Codes Enter Using Finger Gesture Recognition,
DICTA17(1-8)
IEEE DOI 1804
gesture recognition, image sequences, mobile communication, mobile computing, Morse codes enter, Morse codes input, Training BibRef

Gao, B., Kim, H., Lee, H., Lee, J., Kim, J.,
Effects of Continuous Auditory Feedback on Drawing Trajectory-Based Finger Gestures,
HMS(48), No. 6, December 2018, pp. 658-669.
IEEE DOI 1812
feedback, gesture recognition, human computer interaction, touch sensitive screens, finger-attached pen, fat finger issue, visual occlusion BibRef

Chao, F., Huang, Y., Lin, C., Yang, L., Hu, H., Zhou, C.,
Use of Automatic Chinese Character Decomposition and Human Gestures for Chinese Calligraphy Robots,
HMS(49), No. 1, February 2019, pp. 47-58.
IEEE DOI 1901
Writing, Trajectory, Manipulators, Databases, Service robots, Hardware, Chinese character decomposition, human-robot interactions, robotic calligraphy BibRef


Kwolek, B.[Bogdan], Sako, S.[Shinji],
Learning Siamese Features for Finger Spelling Recognition,
ACIVS17(225-236).
Springer DOI 1712
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, 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:Aug 10, 2019 at 15:07:15