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  1. Електронний науковий архів Науково-технічної бібліотеки Національного університету "Львівська політехніка"
  2. Електронний архів Науково-технічної бібліотеки
  3. Матеріали конференцій
  4. Data stream mining and processing : proceedings of the IEEE second international conference
  5. Data stream mining and processing : proceedings of the IEEE second international conference

putin IS MURDERER

Please use this identifier to cite or link to this item: https://oldena.lpnu.ua/handle/ntb/52537
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dc.contributor.authorKondratiuk, Sergii
dc.contributor.authorKrak, Iurii
dc.coverage.temporal21-25 August 2018, Lviv
dc.date.accessioned2020-06-19T12:05:57Z-
dc.date.available2020-06-19T12:05:57Z-
dc.date.created2018-02-28
dc.date.issued2018-02-28
dc.identifier.citationKondratiuk S. Dactyl Alphabet Modeling and Recognition Using Cross Platform Software / Sergii Kondratiuk, Iurii Krak // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 420–423. — (Hybrid Systems of Computational Intelligence).
dc.identifier.isbn© Національний університет „Львівська політехніка“, 2018
dc.identifier.isbn© Національний університет „Львівська політехніка“, 2018
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/52537-
dc.description.abstractThe technology, which is implemented with cross platform tools, is proposed for modeling of gesture units of sign language, animation between states of gesture units with a combination of gestures (words). Implemented technology simulates sequence of gestures using virtual spatial hand model and performs recognition of dactyl items from camera input. With the cross platform means technology achieves the ability to run on multiple platforms without re-implementing for each platform.
dc.format.extent420-423
dc.language.isoen
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofData stream mining and processing : proceedings of the IEEE second international conference, 2018
dc.relation.urihttp://www.patentlyapple.com/patently-apple/2014/12/apple-invents-a-highlyadvanced-air-gesturing-system-for-future-idevices-and-beyond.html
dc.subjectcross platform
dc.subjectsing language
dc.subjectdactyl modeling
dc.subjectgesture recognition
dc.titleDactyl Alphabet Modeling and Recognition Using Cross Platform Software
dc.typeConference Abstract
dc.rights.holder© Національний університет “Львівська політехніка”, 2018
dc.contributor.affiliationTaras Shevchenko National University
dc.format.pages4
dc.identifier.citationenKondratiuk S. Dactyl Alphabet Modeling and Recognition Using Cross Platform Software / Sergii Kondratiuk, Iurii Krak // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 420–423. — (Hybrid Systems of Computational Intelligence).
dc.relation.references[1] P. Mell and T. Grance, ”The NIST Definition of Cloud Computing,” (Technical report), National Institute of Standards and Technology: U.S. Department of Commerce, pp. 1-7, September 2011. doi:10.6028/NIST.SP.800-145. Special publication 800-145.
dc.relation.references[2] The Linux Information Project, Cross-platform Definition.
dc.relation.references[3] J. Smith, and R. Nair, “The Architecture of Virtual Machines,” Computer, vol. 38, no 5, pp. 32–38, 2005.
dc.relation.references[4] ASL Sing language dictionary www.signasl.org/sign/model
dc.relation.references[5] L. A. Graschenko, A. P. Fisun and et., Teoreticheskie i prakticheskie osnovyi cheloveko-kompyuternogo vzaimodeystviya: bazovyie ponyatiya cheloveko-kompyuternyih sistem v informatike i informatsionnoy bezopasnosti: Monografiya / Red. A. P. Fisun. Orel: OGU, 2004. Dep. v VINITI 15.10.2004 g. # 1624 — V2004
dc.relation.references[6] Samsung TV Gesture book www.samsung.com/ph/smarttv/common/guide_book_3p_si/waving.html
dc.relation.references[7] Apple Touchless Gesture System for iDevices http://www.patentlyapple.com/patently-apple/2014/12/apple-invents-a-highlyadvanced-air-gesturing-system-for-future-idevices-and-beyond.html
dc.relation.references[8] R. Z. Khan, I. A. Noor, “Comparative study of hand gesture recognition system,” Natarajan Meghanathan, et al. (Eds): SIPM, FCST, ITCA, WSE, ACSIT, CS & IT 06, pp. 203–213, 2012.
dc.relation.references[9] M. Neff, M. Kipp, I. Albrecht, and H.-P., “Seidel Gesture Modeling and Animation by Imitation,” Technical Report MPI-I-2006-1-005, Max-Planck-Institut Informatik, Saabrucken, Germany, 2006.
dc.relation.references[10] A. Shapiro, D. Chu, B. Allen, and P. Faloutsos, “A Dynamic Controller Toolkit,” Sandbox '07 Proceedings of the 2007 ACM SIGGRAPH symposium on Video games, , San Diego, California, pp. 15-20, August 04 - 05, 2007
dc.relation.references[11] Iu. G. Kryvonos, Yu. V. Krak, Yu. V. Barchukova, and B. A.Trocenko, “Human Hand Motion Parametrization for Dactilemes Modeling,” Journal of Automation and Information Sciences, vol. 43, no. 12, pp.1-11, 2011.
dc.relation.references[12] O. Aran, I. Ari, A. Benoit, A. Huerta Carrillo, F.-X. Fanard, P. Campr, L. Akarun, A. Caplier, M. Rombaut and B. Sankur, “Sing language tutoring tool,” 2006 eNTERFACE’06, Dubrovnik, Croatia. Final Project Report, July 17 – August 11, pp. 1-11, 2006.
dc.relation.references[13] J.L. Raheja, A.S Sadab and A. Chaudhary, “Android based portable hand sign recognition system,” Ed: A. Chaudhary, Recent Trends in Hand Gesture Recognition, GCSR, vol. 3, pp. 1-18, 2015. DOI: 10.15579/gcsr.vol3.ch1,
dc.relation.references[14] W. C. Stokoe, “Sign Language Structure,” An Outline of the Visual Communication Systems of the American Deaf., p.61-67, 1960.
dc.relation.references[15] Unity3D framework www.unity3d.com
dc.relation.references[16] Tensorflow framework documentation www.tensorflow.org/api/
dc.relation.references[17] R. Tubiana, J. Thomine, and E. Mackin, Examination of the hand and wrist. 2nd ed. Martin Dunitz, 1996. ISBN: 1853175447/1-85317-544-7. Publisher: Informa Healthcare
dc.relation.references[18] YAML – The Official YAML Web Site www.yaml.org
dc.relation.references[19] O. Koller, J. Forster, and H. Ney, “Continuous sign language recognition: Towards large vocabulary statistical recognition systems handling multiple signers,” Computer Vision and Image Understanding, vol. 141, pp. 108–125, 2015.
dc.relation.references[20] P. Dreuw, D. Rybach, T. Deselaers, M. Zahedi, and H. Ney, “Speech recognition techniques for a sign language recognition system,” In Interspeech, Antwerp, Belgium, ISCA best student paper award Interspeech 2007, pp. 2513-2516, August 2007.
dc.relation.references[21] Eng-Jon Ong et al. “Sign language recognition using sequential pattern trees,” 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2200–2207, 2012.
dc.relation.references[22] A. Agarwal, and M. Thakur, “Sign Language Recognition using Microsoft Kinect,” IEEE International Conference on Contemporary Computing, pp. 181-185, 2013.
dc.relation.references[23] L. Pigou, S. Dieleman, P.-J. Kindermans, and B. Schrauwen, "Italian Sign language: Sign Language Recognition Using Convolutional Neural Networks. ELIS, Ghent University, Ghent, Belgium, 2015
dc.relation.references[24] Brandon Garcia, and Sigberto Alarcon Viesca, American Sign language: Real-time American Sign Language Recognition with Convolutional Neural Networks Stanford University Stanford, CA, pp. 225-232, 2015.
dc.relation.references[25] V. Bobic, “Hand gesture recognition using neural network based techniques,” School of Electrical Engineering, University of Belgrade, 2016.
dc.relation.references[26] PostgreSQL official web site www.postgresql.org
dc.relation.referencesen[1] P. Mell and T. Grance, "The NIST Definition of Cloud Computing," (Technical report), National Institute of Standards and Technology: U.S. Department of Commerce, pp. 1-7, September 2011. doi:10.6028/NIST.SP.800-145. Special publication 800-145.
dc.relation.referencesen[2] The Linux Information Project, Cross-platform Definition.
dc.relation.referencesen[3] J. Smith, and R. Nair, "The Architecture of Virtual Machines," Computer, vol. 38, no 5, pp. 32–38, 2005.
dc.relation.referencesen[4] ASL Sing language dictionary www.signasl.org/sign/model
dc.relation.referencesen[5] L. A. Graschenko, A. P. Fisun and et., Teoreticheskie i prakticheskie osnovyi cheloveko-kompyuternogo vzaimodeystviya: bazovyie ponyatiya cheloveko-kompyuternyih sistem v informatike i informatsionnoy bezopasnosti: Monografiya, Red. A. P. Fisun. Orel: OGU, 2004. Dep. v VINITI 15.10.2004 g. # 1624 - V2004
dc.relation.referencesen[6] Samsung TV Gesture book www.samsung.com/ph/smarttv/common/guide_book_3p_si/waving.html
dc.relation.referencesen[7] Apple Touchless Gesture System for iDevices http://www.patentlyapple.com/patently-apple/2014/12/apple-invents-a-highlyadvanced-air-gesturing-system-for-future-idevices-and-beyond.html
dc.relation.referencesen[8] R. Z. Khan, I. A. Noor, "Comparative study of hand gesture recognition system," Natarajan Meghanathan, et al. (Eds): SIPM, FCST, ITCA, WSE, ACSIT, CS & IT 06, pp. 203–213, 2012.
dc.relation.referencesen[9] M. Neff, M. Kipp, I. Albrecht, and H.-P., "Seidel Gesture Modeling and Animation by Imitation," Technical Report MPI-I-2006-1-005, Max-Planck-Institut Informatik, Saabrucken, Germany, 2006.
dc.relation.referencesen[10] A. Shapiro, D. Chu, B. Allen, and P. Faloutsos, "A Dynamic Controller Toolkit," Sandbox '07 Proceedings of the 2007 ACM SIGGRAPH symposium on Video games, , San Diego, California, pp. 15-20, August 04 - 05, 2007
dc.relation.referencesen[11] Iu. G. Kryvonos, Yu. V. Krak, Yu. V. Barchukova, and B. A.Trocenko, "Human Hand Motion Parametrization for Dactilemes Modeling," Journal of Automation and Information Sciences, vol. 43, no. 12, pp.1-11, 2011.
dc.relation.referencesen[12] O. Aran, I. Ari, A. Benoit, A. Huerta Carrillo, F.-X. Fanard, P. Campr, L. Akarun, A. Caplier, M. Rombaut and B. Sankur, "Sing language tutoring tool," 2006 eNTERFACE’06, Dubrovnik, Croatia. Final Project Report, July 17 – August 11, pp. 1-11, 2006.
dc.relation.referencesen[13] J.L. Raheja, A.S Sadab and A. Chaudhary, "Android based portable hand sign recognition system," Ed: A. Chaudhary, Recent Trends in Hand Gesture Recognition, GCSR, vol. 3, pp. 1-18, 2015. DOI: 10.15579/gcsr.vol3.ch1,
dc.relation.referencesen[14] W. C. Stokoe, "Sign Language Structure," An Outline of the Visual Communication Systems of the American Deaf., p.61-67, 1960.
dc.relation.referencesen[15] Unity3D framework www.unity3d.com
dc.relation.referencesen[16] Tensorflow framework documentation www.tensorflow.org/api/
dc.relation.referencesen[17] R. Tubiana, J. Thomine, and E. Mackin, Examination of the hand and wrist. 2nd ed. Martin Dunitz, 1996. ISBN: 1853175447/1-85317-544-7. Publisher: Informa Healthcare
dc.relation.referencesen[18] YAML – The Official YAML Web Site www.yaml.org
dc.relation.referencesen[19] O. Koller, J. Forster, and H. Ney, "Continuous sign language recognition: Towards large vocabulary statistical recognition systems handling multiple signers," Computer Vision and Image Understanding, vol. 141, pp. 108–125, 2015.
dc.relation.referencesen[20] P. Dreuw, D. Rybach, T. Deselaers, M. Zahedi, and H. Ney, "Speech recognition techniques for a sign language recognition system," In Interspeech, Antwerp, Belgium, ISCA best student paper award Interspeech 2007, pp. 2513-2516, August 2007.
dc.relation.referencesen[21] Eng-Jon Ong et al. "Sign language recognition using sequential pattern trees," 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2200–2207, 2012.
dc.relation.referencesen[22] A. Agarwal, and M. Thakur, "Sign Language Recognition using Microsoft Kinect," IEEE International Conference on Contemporary Computing, pp. 181-185, 2013.
dc.relation.referencesen[23] L. Pigou, S. Dieleman, P.-J. Kindermans, and B. Schrauwen, "Italian Sign language: Sign Language Recognition Using Convolutional Neural Networks. ELIS, Ghent University, Ghent, Belgium, 2015
dc.relation.referencesen[24] Brandon Garcia, and Sigberto Alarcon Viesca, American Sign language: Real-time American Sign Language Recognition with Convolutional Neural Networks Stanford University Stanford, CA, pp. 225-232, 2015.
dc.relation.referencesen[25] V. Bobic, "Hand gesture recognition using neural network based techniques," School of Electrical Engineering, University of Belgrade, 2016.
dc.relation.referencesen[26] PostgreSQL official web site www.postgresql.org
dc.citation.conferenceIEEE second international conference "Data stream mining and processing"
dc.citation.spage420
dc.citation.epage423
dc.coverage.placenameЛьвів
Appears in Collections:Data stream mining and processing : proceedings of the IEEE second international conference

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