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| Chung-Hsien Wu, Yu-Hsien Chiu, Kung-Wei Cheng, "Error-Tolerant Sign Retrieval Using Visual Features and Maximum A Posteriori Estimation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 4, pp. 495-508, April, 2004. | |||
| BibTex | x | ||
| @article{ 10.1109/TPAMI.2004.1265864, author = {Chung-Hsien Wu and Yu-Hsien Chiu and Kung-Wei Cheng}, title = {Error-Tolerant Sign Retrieval Using Visual Features and Maximum A Posteriori Estimation}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {26}, number = {4}, issn = {0162-8828}, year = {2004}, pages = {495-508}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2004.1265864}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Error-Tolerant Sign Retrieval Using Visual Features and Maximum A Posteriori Estimation IS - 4 SN - 0162-8828 SP495 EP508 EPD - 495-508 A1 - Chung-Hsien Wu, A1 - Yu-Hsien Chiu, A1 - Kung-Wei Cheng, PY - 2004 KW - Taiwanese Sign Language KW - alternative and augmentative communication KW - error tolerant retrieval KW - gesture feature. VL - 26 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—This paper proposes an efficient error-tolerant approach to retrieving sign words from a Taiwanese Sign Language (TSL) database. This database is tagged with visual gesture features and organized as a multilist code tree. These features are defined in terms of the visual characteristics of sign gestures by which they are indexed for sign retrieval and displayed using an anthropomorphic interface. The maximum a posteriori estimation is exploited to retrieve the most likely sign word given the input feature sequence. An error-tolerant mechanism based on mutual information criterion is proposed to retrieve a sign word of interest efficiently and robustly. A user-friendly anthropomorphic interface is also developed to assist learning TSL. Several experiments were performed in an educational environment to investigate the system's retrieval accuracy. Our proposed approach outperformed a dynamic programming algorithm in its task and shows tolerance to user input errors.
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