A person independent system for recognition of hand postures used in sign language

Pattern Recognition Letters

Volumn 31, Issue 11, 2010, Pages 1359-1368

  Kelly, Daniel ^a   McDonald, John ^a   Markham, Charles ^a  

^a NATIONAL UNIVERSITY OF IRELAND   (Ireland)

Author keywords

Classifier design and evaluation; Feature representation; Moments; Object recognition; Size and shape; Tracking

Indexed keywords

CLASSIFIER DESIGN AND EVALUATION; DATA SETS; EIGENSPACES; FEATURE REPRESENTATION; HAND POSTURE; HAND POSTURE RECOGNITION; HU MOMENTS; PERSON-INDEPENDENT; SIGN LANGUAGE; SIZE AND SHAPE; SIZE FUNCTIONS;

CLASSIFIERS; LINGUISTICS; OBJECT RECOGNITION;

FUNCTION EVALUATION;

EID: 77953133447     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2010.02.004     Document Type: Article

References (33)

1. Aizerman A., Braverman E.M., and Rozoner L.I. Theoretical foundations of the potential function method in pattern recognition learning. Automation Remote Control 25 (1964) 821-837
2. Al-Jarrah O., and Halawani A. Recognition of gestures in Arabic sign language using neuro-fuzzy systems. Artif. Intell. 133 1-2 (2001) 117-138 ISSN 0004-3702
3. Bauer, B., Hienz, H., 2000. Relevant features for video-based continuous sign language recognition. In: FG '00. IEEE Computer Society, Washington, DC, USA, p. 440. ISBN: 0-7695-0580-5.
4. Chang, C.-C., Lin, C.-J., 2001. LIBSVM: A library for support vector machines. Available from: .
5. Comaniciu, D., Ramesh, V., Meer, P., 2000. Real-time tracking of non-rigid objects using mean shift. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition 2, 142-149. doi:10.1109/CVPR.2000.854761.
6. Cooper, H., Bowden, R., 2007. Large Lexicon detection of sign language. In: CVHCI07, pp. 88-97.
7. Cui Y., and Weng J. Appearance-based hand sign recognition from intensity image sequences. CVIU 78 2 (2000) 157-176
8. Deng, J.-W., Tsui, H., 2002. A novel two-layer PCA/MDA scheme for hand posture recognition. In: Proc. Pattern Recognition, Vol. 1, pp. 283-286. doi:10.1109/ICPR.2002.1044688, ISSN: 1051-4651.
9. fan Wu T., Jen Lin C., and Weng R.C. Probability estimates for multi-class classification by pairwise coupling. J. Machine Learn. Res. 5 (2004) 975-1005
10. Farhadi, A., Forsyth, D., White, R., 2007. Transfer learning in sign language. In: IEEE Conf. on Computer Vision and Pattern Recognition, CVPR '07, pp. 1-8.
11. Handouyahia, M., Ziou, D., Wang, S., 1999. Sign language recognition using moment-based size functions. In: Proc. Intl. Conf. on Vision Interface, pp. 210-216.
12. Holden, E.-J., Owens, R., 2003. Recognising moving hand shapes. Proc. Image Analysis and Processing, pp. 14-19. doi: 10.1109/ICIAP.2003.1234018.
13. Holden, E.-J., Lee, G., Owens, R., 2005. Automatic recognition of colloquial australian sign language. In: IEEE Workshop on Motion and Video Computing, WACV/MOTIONS '05, Vol. 2, pp. 183-188. doi: 10.1109/ACVMOT.2005.30.
14. Hu M.-K. Visual pattern recognition by moment invariants, information theory. IEEE Trans. 8 2 (1962) 179-187 ISSN 0018-9448
15. Huang C.-L., and Huang W.-Y. Sign language recognition using model-based tracking and a 3D hopfield neural network. Mach. Vision Appl. 10 5-6 (1998) 292-307 http://dx.doi.org/10.1007/s00138005008, ISSN 0932-8092
16. Imagawa, I., Matsuo, H., Taniguchi, R., Arita, D., Lu, S., Igi, S., 2000. Recognition of local features for camera-based sign language recognition system. In: Proc. Pattern Recognition, Vol. 4, pp. 849-853. doi: 10.1109/ICPR.2000.903050.
17. Intel-Corporation, 2000. Open Source Computer Vision Library: Reference Manual.
18. Just, A., Rodriguez, Y., Marcel, S., 2006. Hand posture classification and recognition using the modified census transform. In: 7th Internat. Conf. on Automatic Face and Gesture Recognition, FGR, pp. 351-356. doi: 10.1109/FGR.2006.62.
19. Kadir, T., Bowden, R., Ong, E.J., Zisserman, A., 2004. Minimal training, large lexicon unconstrained sign language recognition. In: BMVC.
20. Kelly, D., McDonald, J., Markham, C., 2008. A system for teaching sign language using live gesture feedback. In: 8th IEEE Internat. Conf. on FG '08, pp. 1-2.
21. Licsr A., and Szirnyi T. User-adaptive hand gesture recognition system with interactive training. Image Vision Comput. 23 12 (2005) 1102-1114 10.1016/j.imavis.2005.07.01 ISSN 0262-8856
22. Lin H.-T., Lin C.-J., and Weng R.C. A note on Platt's probabilistic outputs for support vector machines. Mach. Learn. 68 3 (2007) 267-276 ISSN 0885-6125
23. Patwardhan K.S., and Roy S.D. Hand gesture modelling and recognition involving changing shapes and trajectories, using a predictive EigenTracker. Pattern Recognition Lett. 28 3 (2007) 329-334 ISSN 0167-8655
24. Pavlovic V., Sharma R., and Huang T. Visual interpretation of hand gestures for human-computer interaction: A review. IEEE PAMI 19 7 (1997) 677-695 10.1109/34.59822 ISSN 0162-8828
25. Platt J.C., and Platt J.C. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Advances in Large Margin Classifiers (1999), MIT Press
26. Starner T., Pentland A., and Weaver J. Real-time american sign language recognition using desk and wearable computer based video. IEEE PAMI 20 12 (1998) 1371-1375 http://dx.doi.org/10.1109/34.73581, ISSN: 0162-8828
27. Stokoe J., and William C. Sign language structure: An outline of the visual communication systems of the american deaf. J. Deaf Stud. Deaf Educ. 10 1 (2005) 3-37 ISSN: 1081-4159
28. Suzuki S., and Be K. Topological structural analysis of digitized binary images by border following. Comput. Vision Graphics Image Process. 30 1 (1985) 32-46
29. Tanibata, N., Shimada, N., Shirai, Y., 2002. Extraction of hand features for recognition of sign language words. In: Internat. Conf. on Vision Interface, pp. 391-398.
30. Triesch J., and von der Malsburg C. Classification of hand postures against complex backgrounds using elastic graph matching. Image Vision Comput. 20 13-14 (2002) 937-943
31. Uras, C., Verri, A., 1995. Sign language recognition: An application of the theory of size functions. In: 6th British Machine Vision Conference, pp. 711-720.
32. Wu Y., Huang T.S., and Mathews N. Vision-based gesture recognition: A review. Lecture Notes in Computer Science (1999), Springer 103-115
33. Yang, H.D., Sclaroff, S., Lee, S.W., 2009. Sign language spotting with a threshold model based on conditional random fields. In: IEEE PAMI 99 (1).