Movement Epenthesis Generation Using NURBS-Based Spatial Interpolation

Chuang, Ze-Jing; Wu, Chung-Hsien; Chen, Weisheng

doi:10.1109/tcsvt.2006.883509

Cited by 13 publications

(3 citation statements)

References 14 publications

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“…However, all such data contains Movement Epenthesis (ME) [7] [26]. During the production of a sign language sentence, it is often the case that a movement segment needs to be inserted between two consecutive signs to move the hands from the end of one sign to the beginning of the next.…”

Section: A Why Clustering Time Series Streams Requires Ignoring Somementioning

confidence: 99%

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data

Rakthanmanon

Keogh

Lonardi

et al. 2011

2011 IEEE 11th International Conference on Data Mining

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Abstract-Given the pervasiveness of time series data in all human endeavors, and the ubiquity of clustering as a data mining application, it is somewhat surprising that the problem of time series clustering from a single stream remains largely unsolved. Most work on time series clustering considers the clustering of individual time series, e.g., gene expression profiles, individual heartbeats or individual gait cycles. The few attempts at clustering time series streams have been shown to be objectively incorrect in some cases, and in other cases shown to work only on the most contrived datasets by carefully adjusting a large set of parameters. In this work, we make two fundamental contributions. First, we show that the problem definition for time series clustering from streams currently used is inherently flawed, and a new definition is necessary. Second, we show that the Minimum Description Length (MDL) framework offers an efficient, effective and essentially parameter-free method for time series clustering. We show that our method produces objectively correct results on a wide variety of datasets from medicine, zoology and industrial process analyses.

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Section: A Why Clustering Time Series Streams Requires Ignoring Somementioning

confidence: 99%

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data

Rakthanmanon

Keogh

Lonardi

et al. 2011

2011 IEEE 11th International Conference on Data Mining

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“…The first technique is joining word-by-word videos of human interpreters (Solina, Krapez, Jaklic & Komac, 2000) and refinements to that technique are suggested in (Chiu, Wu, Su, & Cheng, 2007;Chuang, Wu, & Chen, 2006) for providing a smooth transition between videos.…”

Section: Techniques For Sign Language Synthesis and Animationmentioning

confidence: 99%

Computer Interpreter for Translating Written Sinhala to Sinhala Sign Language

Punchimudiyanse

Meegama

2017

OUSL Jnl

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Sinhala Sign Language (SSL) is the preferred medium of communication amongst the deaf community of Sinhala. A conversational sign in SSL represents a word or phrase in Sinhala whereas a fingerspelling sign represents a character in the Sinhala alphabet. A word in Sinhala has different word forms based on tense and case structure of the Sinhala language. In the early stages of SSL evolution, a single SSL sign represented a base Sinhala word and all its word forms. This technique has deprived essential word form information to a deaf person. The SSL research community has come up with a technique of showing few characters of the expected word form in fingerspelling as prefix and/or suffixes with the sign of the base word to solve the problem. This research paper presents a database driven translator, which implements the said technique by translating written Sinhala sentences into SSL sequences. It gives the opportunity to the SSL research community to popularize this translation technique among SSL users. Moreover, a 3D avatar built earlier for animating spoken Sinhala in SSL is used to animate the translated SSL sequence. A test sample of 100 sentences and a word form database of 500+ entries to match 50 conversational SSL signs (30 nouns and 20 verbs) are formed to test the translator. The database driven search mechanism provided 100% successful translator performance while having 70.83% average sentence identification rate for six SSL users including three professional SSL interpreters.

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“…that need to be concatenated. This approach of synthesizing sign language by concatenation of video clips was later used or further developed by several other creators of sign language dictionaries [18][19][20].…”

Section: Dictionary Of the Slovenian Sign Language On Cd-rommentioning

confidence: 99%

Dictionary of the Slovenian Sign Language on the WWW

Cempre

Besir

Solina

2013

Lecture Notes in Computer Science

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The article describes technical and user-interface issues of transferring the contents and functionality of the CD-ROM version of the Slovenian sing language dictionary to the web. The dictionary of Slovenian sign language consist of video clips showing the demonstration of signs that deaf people use for communication, text description of the words corresponding to the signs and pictures illustrating the same word/sign. A new technical solution-a video sprite-for concatenating subsections of video clips necessary for their smooth display on most available platforms was developed. The contents of the dictionary which were re-edited are combined also with other resources available on the web. Added were also new exercises for learning the sign language.

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Movement Epenthesis Generation Using NURBS-Based Spatial Interpolation

Cited by 13 publications

References 14 publications

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data

Computer Interpreter for Translating Written Sinhala to Sinhala Sign Language

Dictionary of the Slovenian Sign Language on the WWW

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