Transfer learning in sign language

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2007, Pages

  Farhadi, Ali ^a   Forsyth, David ^a   White, Ryan ^b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; DISCRIMINANT ANALYSIS; MATHEMATICAL MODELS; SEMANTICS;

AMERICAN SIGN LANGUAGE (ASL); AVATAR DATA; SIGN LANGUAGE; TRANSFER LEARNING;

LEARNING SYSTEMS;

EID: 34948911163     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2007.383346     Document Type: Conference Paper

References (41)

1. Demographics. Technical report, Gallaudet Research Institute.
2. National institute on deafness and communication disorders: A report of the task force on the national strategic research plan. Federal Register, 57, 1989.
3. S. Akyol and U. Canzler. An information terminal using vision based sign language recognition. In ITEA Workshop on Virtual Home Environments, VHE Middleware Consortium, pages 61-68, 2002.
4. O. Al-Jarrah and A. Halawani. Recognition of gestures in arabic sign language using neuro-fuzzy systems. Artificial Intelligence, 133(1-2):117-138, December 2001.
5. R. K. Ando and T. Zhang. A framework for learning predictive structures from multiple tasks and unlabeled data, volume 6, pages 1817-1853, 2005.
6. R. Battison. Lexical borrowing in American Sign Language. Linstok Press, Silver Spring, MD, 1978.
7. B. Bauer and H. Hienz. Relevant features for video-based continuous sign language recognition. In AFGR, pages 440-445, 2000.
8. J. Baxter. A model of inductive bias learning. J. AIR, 12:149-198, 2000.
9. R. Bowden, D. Windridge, T. Kadir, A. Zisserman, and M. Brady. A linguistic feature vector for the visual interpretation of sign language. In ECCV, pages Vol I: 390-401, 2004.
10. D. Brentari. A prosodic model of sign language phonology. MIT Press, Cambridge, MA, 1998.
11. G. Elidan, G. Heitz, and D. Koller. Learning object shape: From drawings to images. In CVPR '06, pages 2064-2071, Washington, DC, USA, 2006. IEEE Computer Society.
12. K. Emmorey. Language, Congition, and the Brain. Lawrence Erlbaum, Mahwah, NJ, 2002.
13. T. Evgeniou and M. Pontil. Regularized multi-task learning. In KDD '04, pages 109-117, New York, NY, USA, 2004. ACM Press.
14. A. Farhadi and D. Forsyth. Aligning asl for statistical translation using a discriminative word model. In CVPR, 2006.
15. F. Fleuret and G. Blanchard. Pattern recognition from one example by chopping. In NIPS, 2005.
16. W. Gao, J. Ma, X. Chen, et al. Handtalker: a multimodal dialog system using sign language and 3d virtual human. In Proc. Third Int. Conf. Multimodal Interface, pages 564-571, 2000.
17. A. Gelman, J. Carlin, H. Stern, and D. Rubin. Bayesian Data Analysis. Chapman and Hall, 1995.
18. A. Hohenberger, D. Happ, and H. Leuninger. Modality-dependent aspects of sign language production. In R. P. Meier, K. Cormier, and D. Quinto-Pozos, editors, Modality and structure in signed and spoken languages. Cambridge University Press, Cambridge, England, 2002.
19. M. Huenerfauth. A survey and critique of american sign language natural language generation and machine translation systems. Technical report, U. Penn., 2003. TR MS-CIS-03-32.
20. K.Grobel and M.Assan. Isolated sign language recognition using hidden markov models. In Proc. Int. Conf. System Man and Cybernetics, pages 162-167, 1997.
21. J. Kim, W. Jang, and Z. Bien. A dynamic gesture recognition system for the korean sign language (ksl). Systems, Man and Cybernetics-B, 26(2):354-359, April 1996.
22. E. S. Klima and U. Bellugi. The signs of language. Harvard University Press, Cambridge, MA, 1979.
23. D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, November 2004.
24. C. Manning and H. Schütze. Foundations of Statistical Natural Language Processing. MIT Press, 1999.
25. M. Marschark. Psychological development of deaf children. Oxford University Press, 1993.
26. A. M. Martinez, R. B. Wilbur, R. Shay, and A. C. Kak. Purdue rvl-slll asl database for authomatic recognition of amercian sign language. Proc. IEEE Int. Conf. on Multimodal Interfaces, 2002.
27. H. Matsuo, S. Igi, S. Lu, Y. Nagashima, Y. Takata, and T. Teshima. The recognition algorithm with non-contact for Japanese sign language using morphological analysis. In Proc. Int. Gesture Workshop, pages 273-284, 1997.
28. M.W.Kadous. Machine recognition of auslan signs using powergloves: towards large lexicon integration of sign language. In Proc. Workshop on the Integration of Gesture in Language and Speech, pages 165-174, 1996.
29. S. Nayak, S. Sarkar, and B. Loeding. Unsupervised modeling of signs embedded in continuous sentences. In IEEE Workshop on Vision for Human-Computer Interaction in conjunction with CVPR, 2005.
30. G. Obozinski, B. Taskar, and M. I. Jordan. Multi-task feature selection. Technical report, UC Berkeley, 2006.
31. T. Starner, J. Weaver, and A. Pentland. Real-time american sign language recognition using desk and wearable computer based video. PAMI, 20(12): 1371-1375, 1998.
32. A. Steinberg. Issues in providing mental health services to hearing impaired persons. Hosp. Community Psychiatry, (42):380-389, 1991.
33. W. C. Stokoe, D. C. Casterline, and C. G. Croneberg. A dictionary of American Sign Language. Gallaudet University Press, Washington, DC, 1965.
34. S. Thrun. Is learning the n-th thing any easier than learning the first? In Advances in Neural Information Processing Systems 8, 1996.
35. C. Vogler and D. Metaxas. ASL recognition based on a coupling between HMMs and 3D motion analysis. In ICCV, pages 363-369, 1998.
36. C. Vogler and D. Metaxas. Parallel hidden markov models for American sign language recognition. In ICCV, pages 116-122, 1999.
37. C. Vogler and D. Metaxas. Toward scalability in asl recognition: breaking down signs into phonemes. In Gesture workshop 99, 1999.
38. C. Vogler and D. Metaxas. Handshapes and movements: Multiple-channel american sign language recognition. In Proc. Gesture Workshop, pages 247-258, 2003.
39. C. Vogler, H. Sun, and D. Metaxas. A framework for motion recognition with applications to American sign language and gait recognition. In IEEE Workshop on Human Motion, 2000.
40. W.Gao, J. Ma, J. Wu, and C. Wang. Sign language recognition based on hmm/ann/dp. Int. J. Pattern Recognition and Artificial Intelligence, 14(5):587-602, 2000.
41. J. Zieren and K.-F. Kraiss. Non-intrusive sign language recognition for human computer interaction. In Proc. IFAC/IFIP/IFORS/IEA symposium on analysis, design and evaluation of human machine systems, 2004.