Relevant bibliographies by topics / Movement Epenthesis

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Movement Epenthesis'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Movement Epenthesis"

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Geraci, Carlo. "Epenthesis in Italian Sign Language." Sign Language and Linguistics 12, no. 1 (2009): 3–51. http://dx.doi.org/10.1075/sll.12.1.02ger.

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The aim of this study is to provide a detailed account for the phenomenon of movement epenthesis in Italian Sign Language (LIS). LIS displays at least two cases of epenthesis of movement, one affecting signs that involve contact with the body, the other affecting signs that do not (i.e. signs articulated in neutral space). The two cases of epenthesis of movement receive a unified analysis, once the mechanism of selection of the plane of articulation is spelled out. The general phenomenon of movement epenthesis is captured by a formal approach within a constraint-based framework, such as the on
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BHUYAN, M. K., P. K. BORA, and D. GHOSH. "AN INTEGRATED APPROACH TO THE RECOGNITION OF A WIDE CLASS OF CONTINUOUS HAND GESTURES." International Journal of Pattern Recognition and Artificial Intelligence 25, no. 02 (2011): 227–52. http://dx.doi.org/10.1142/s0218001411008592.

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The gesture segmentation is a method that distinguishes meaningful gestures from unintentional movements. Gesture segmentation is a prerequisite stage to continuous gesture recognition which locates the start and end points of a gesture in an input sequence. Yet, this is an extremely difficult task due to both the multitude of possible gesture variations in spatio-temporal space and the co-articulation/movement epenthesis of successive gestures. In this paper, we focus our attention on coping with this problem associated with continuous gesture recognition. This requires gesture spotting that
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Choudhury, Ananya, Anjan Kumar Talukdar, Manas Kamal Bhuyan, and Kandarpa Kumar Sarma. "Movement Epenthesis Detection for Continuous Sign Language Recognition." Journal of Intelligent Systems 26, no. 3 (2017): 471–81. http://dx.doi.org/10.1515/jisys-2016-0009.

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AbstractAutomatic sign language recognition (SLR) is a current area of research as this is meant to serve as a substitute for sign language interpreters. In this paper, we present the design of a continuous SLR system that can extract out the meaningful signs and consequently recognize them. Here, we have used height of the hand trajectory as a salient feature for separating out the meaningful signs from the movement epenthesis patterns. Further, we have incorporated a unique set of spatial and temporal features for efficient recognition of the signs encapsulated within the continuous sequence
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Chuang, Ze-Jing, Chung-Hsien Wu, and Wei-Sheng Chen. "Movement Epenthesis Generation Using NURBS-Based Spatial Interpolation." IEEE Transactions on Circuits and Systems for Video Technology 16, no. 11 (2006): 1313–23. http://dx.doi.org/10.1109/tcsvt.2006.883509.

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Cardinaletti, Anna, and Lori Repetti. "The Phonology and Syntax of Preverbal and Postverbal Subject Clitics in Northern Italian Dialects." Linguistic Inquiry 39, no. 4 (2008): 523–63. http://dx.doi.org/10.1162/ling.2008.39.4.523.

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We argue that preverbal and postverbal subject clitics in northern Italian dialects are the same lexical items. The different forms of proclitics and enclitics can be explained phonologically (i.e., by phonological constraints ranked in a particular order) and by the hypothesis that morphologically neutral vowels may be inserted in final position (what we call morphological epenthesis). The distributional differences in the paradigm derive from a competition between overt clitics and null subjects that is resolved in an intricate way across sentence types and across dialects and that depends o
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Yang, R., S. Sarkar, and B. Loeding. "Handling Movement Epenthesis and Hand Segmentation Ambiguities in Continuous Sign Language Recognition Using Nested Dynamic Programming." IEEE Transactions on Pattern Analysis and Machine Intelligence 32, no. 3 (2010): 462–77. http://dx.doi.org/10.1109/tpami.2009.26.

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GAO, WEN, JIYONG MA, JIANGQIN WU, and CHUNLI WANG. "SIGN LANGUAGE RECOGNITION BASED ON HMM/ANN/DP." International Journal of Pattern Recognition and Artificial Intelligence 14, no. 05 (2000): 587–602. http://dx.doi.org/10.1142/s0218001400000386.

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In this paper, a system designed for helping the deaf to communicate with others is presented. Some useful new ideas are proposed in design and implementation. An algorithm based on geometrical analysis for the purpose of extracting invariant feature to signer position is presented. An ANN–DP combined approach is employed for segmenting subwords automatically from the data stream of sign signals. To tackle the epenthesis movement problem, a DP-based method has been used to obtain the context-dependent models. Some techniques for system implementation are also given, including fast matching, fr
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Elakkiya, R., and K. Selvamani. "An Active Learning Framework for Human Hand Sign Gestures and Handling Movement Epenthesis Using Enhanced Level Building Approach." Procedia Computer Science 48 (2015): 606–11. http://dx.doi.org/10.1016/j.procs.2015.04.142.

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Choudhury, Ananya, Anjan Kumar Talukdar, Kandarpa Kumar Sarma, and M. K. Bhuyan. "An Adaptive Thresholding-Based Movement Epenthesis Detection Technique Using Hybrid Feature Set for Continuous Fingerspelling Recognition." SN Computer Science 2, no. 2 (2021). http://dx.doi.org/10.1007/s42979-021-00544-5.

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Dissertations / Theses on the topic "Movement Epenthesis"

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Yang, Ruiduo. "Dynamic programming with multiple candidates and its applications to sign language and hand gesture recognition." [Tampa, Fla.] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002310.

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Conference papers on the topic "Movement Epenthesis"

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Kelly, Daniel, John McDonald, and Charles Markham. "Recognizing Spatiotemporal Gestures and Movement Epenthesis in Sign Language." In 2009 13th International Machine Vision and Image Processing Conference. IEEE, 2009. http://dx.doi.org/10.1109/imvip.2009.33.

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Chuang, Ze-Jing, Chung-Hsien Wu, and Wei-Sheng Chen. "Movement Epenthesis Generation for Sign Language Synthesis Using NURBS Function." In TENCON 2006 - 2006 IEEE Region 10 Conference. IEEE, 2006. http://dx.doi.org/10.1109/tencon.2006.343690.

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Yang, Ruiduo, Sudeep Sarkar, and Barbara Loeding. "Enhanced Level Building Algorithm for the Movement Epenthesis Problem in Sign Language Recognition." In 2007 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2007. http://dx.doi.org/10.1109/cvpr.2007.383347.

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Nayan, Navneet, D. Ghosh, and P. M. Pradhan. "An Optical Flow Based Approach to Detect Movement Epenthesis in Continuous Fingerspelling of Sign Language." In 2021 National Conference on Communications (NCC). IEEE, 2021. http://dx.doi.org/10.1109/ncc52529.2021.9530076.

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Talukdar, Anjan Kumar, and M. K. Bhuyan. "Movement Epenthesis Detection in Continuous Fingerspelling from a Coarsely Sampled Motion Vector Field in H.264/AVC Video." In 2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS). IEEE, 2018. http://dx.doi.org/10.1109/raics.2018.8634902.

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Elakkiya, R., K. Selvamani, and S. Kanimozhi. "Notice of Violation of IEEE Publication Principles: Hand gesture recognition framework for recognizing sign gestures and handling movement epenthesis using Level Building nested dynamic programming approach." In 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2014. http://dx.doi.org/10.1109/ccece.2014.6901162.

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