[go: up one dir, main page]

Skip to main content

Intangible Cultural Heritage and New Technologies: Challenges and Opportunities for Cultural Preservation and Development

  • Chapter
  • First Online:
Mixed Reality and Gamification for Cultural Heritage

Abstract

Intangible cultural heritage (ICH) is a relatively recent term coined to represent living cultural expressions and practices, which are recognised by communities as distinct aspects of identity. The safeguarding of ICH has become a topic of international concern primarily through the work of United Nations Educational, Scientific and Cultural Organization (UNESCO). However, little research has been done on the role of new technologies in the preservation and transmission of intangible heritage. This chapter examines resources, projects and technologies providing access to ICH and identifies gaps and constraints. It draws on research conducted within the scope of the collaborative research project, i-Treasures. In doing so, it covers the state of the art in technologies that could be employed for access, capture and analysis of ICH in order to highlight how specific new technologies can contribute to the transmission and safeguarding of ICH.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. F. Cameron, S. Kenderdine, Theorizing Digital Cultural Heritage: A Critical Discourse (MIT Press, Cambridge, 2010)

    Google ScholarĀ 

  2. M. Ioannides, D. Fellner, A. Georgopoulos, D. Hadjimitsis (ed.), Digital Heritage, in 3rd International Conference, Euromed 2010, Lemnos, Cyprus, Proceedings (Springer, Berlin, 2010)

    Google ScholarĀ 

  3. K. Dimitropoulos, S. Manitsaris, F. Tsalakanidou, S. Nikolopoulos, B. Denby, S. Al Kork, L. Crevier-Buchman, C. Pillot-Loiseau, S. Dupont, J. Tilmanne, M. Ott, M. Alivizatou, E. Yilmaz, L. Hadjileontiadis, V. Charisis, O. Deroo, A. Manitsaris, I. Kompatsiaris, N. Grammalidis, Capturing the intangible: an introduction to the i-treasures project, in Proceedings of 9th International Conference on Computer Vision Theory and Applications (VISAPP2014), Lisbon, 5ā€“8 Jan 2014

    Google ScholarĀ 

  4. N. Aikawa, An historical overview of the preparation of the UNESCO international convention for the safeguarding of intangible heritage. Museum Int. 56, 137ā€“149 (2004)

    ArticleĀ  Google ScholarĀ 

  5. V. Hafstein, Intangible heritage as list: from masterpieces to representation, in Intangible heritage, ed. by L. Smith, N. Akagawa (Routledge, Abingdon, 2009), pp. 93ā€“111

    Google ScholarĀ 

  6. P. Nas, Masterpieces of oral and intangible heritage: reflections on the UNESCO world heritage list. Curr. Anthropol. 43(1), 139ā€“143 (2002)

    ArticleĀ  Google ScholarĀ 

  7. M. Alivizatou, The UNESCO programme for the proclamation of masterpieces of the oral and intangible heritage of humanity: a critical examination. J. Museum Ethnogr. 19, 34ā€“42 (2007)

    Google ScholarĀ 

  8. L. Bolton, Unfolding the Moon: Enacting Womenā€™s Kastom in Vanuatu (University of Hawaiā€™i Press, Honolulu, 2003)

    Google ScholarĀ 

  9. K. Huffman, The fieldworkers of the Vanuatu cultural centre and their contribution to the audiovisual collections, in Arts of Vanuatu, ed. by J. Bonnemaison, K. Huffman, D. Tryon (University of Hawaiā€™i Press, Honolulu, 1996), pp. 290ā€“293

    Google ScholarĀ 

  10. S. Zafeiriou, L. Yin, 3D facial behaviour analysis and understanding. Image Vis. Comput. 30, 681ā€“682 (2012)

    ArticleĀ  Google ScholarĀ 

  11. P. Ekman, R. Levenson, W. Friesen, Emotions differ in autonomic nervous system activity. Science 221, 1208ā€“1210 (1983)

    ArticleĀ  Google ScholarĀ 

  12. O. Engwall, Modeling of the vocal tract in three dimensions, in Proceedings, Eu-rospeech99, Hungary, 1999, pp. 113116

    Google ScholarĀ 

  13. S.Fels, J.E. Lloyd, K. Van Den Doel, F. Vogt, I. Stavness, E. Vatikiotis-Bateson, Developing physically-based, dynamic vocal tract models using Artisynth, in Proceedings of ISSP 6, 1991, pp. 419ā€“426

    Google ScholarĀ 

  14. M. Stone, Toward a model of three-dimensional tongue movement. Phonetics 19, 309320 (1991)

    Google ScholarĀ 

  15. P. Badin, G. Bailly, L. Reveret, M. Baciu, C. Segebarth, C. Savariaux, Three-dimensional linear articulatory modeling of tongue, lips and face, based on MRI and video images. J. Phon. 30(3), 533ā€“553 (2002)

    ArticleĀ  Google ScholarĀ 

  16. M. Stone, A three-dimensional model of tongue movement based on ultrasound and X-ray microbeam data. J. Acoust. Soc. Am. 87, 2207 (1990)

    ArticleĀ  Google ScholarĀ 

  17. O. Engwall, From real-time MRI to 3D tongue movements, in Proceedings, 8th International Conference on Spoken Language Processing (ICSLP), Jeju Island, Vol. 2, 2004, pp. 1109ā€“1112

    Google ScholarĀ 

  18. M. Stone, A. Lundberg, Three-dimensional tongue surface shapes of English consonants and vowels. J. Acoust. Soc. Am. 99(6), 37283737 (1996)

    ArticleĀ  Google ScholarĀ 

  19. N. Henrich, B. Lortat-Jacob, M. Castellengo, L. Bailly, X Pelorson, Period-doubling occurences in singing: the ā€œbassuā€ case in traditional Sardinian ā€œA Tenoreā€ singing, in Proceedings of the International Conference on Voice Physiology and Biomechanics, Tokyo, July 2006

    Google ScholarĀ 

  20. N. Henrich, L. Bailly, X. Pelorson, B. Lortat-Jacob, Physiological and physical understanding of singing voice practices: the Sardinian Bassu case, AIRS Start-up meeting, Prince Edward Island, 2009

    Google ScholarĀ 

  21. W. Cho, J. Hong, H. Park, Real-time ultrasonographic assessment of true vocal fold length in professional singers. J. Voice 26(6), 1ā€“6 (2012)

    ArticleĀ  Google ScholarĀ 

  22. G. Troup, T. Griffiths, M. Schneider-Kolsky, T. Finlayson, Ultrasound observation of vowel tongue shapes in trained singers, in Proceedings of the 30th Condensed Matter and Materials Meeting, Wagga, 2006

    Google ScholarĀ 

  23. T. Coduys, C. Henry, A. Cont, TOASTER and KROONDE: high-resolution and high-speed real-time sensor interfaces, in Proceedings of the Conference on New Interfaces for Musical Expression, Singapore, 2004, pp. 205ā€“206

    Google ScholarĀ 

  24. F. Bevilacqua, B. Zamborlin, A. Sypniewski, N. Schnell, F. Guedy, N. Rasamimanana, Gesture in embodied communication and human-computer interaction, in 8th International Gesture Workshop, 2010, pp. 73ā€“84

    Google ScholarĀ 

  25. M. Caon, Context-aware 3D gesture interaction based on multiple kinects, in Proceedings of the First International Conference on Ambient Computing, Applications, Services and Technologies, Barcelona, 2011, pp. 7ā€“12

    Google ScholarĀ 

  26. M. Boucher, Virtual dance and motion-capture. Contemp. Aesthet. 9, 10 (2011)

    Google ScholarĀ 

  27. R. Aylward, J.A. Paradiso, Sensemble: a wireless, compact, multi-user sensor system for interactive dance, in Proceedings of the International Conference on New Interfaces for Musical Expression (NIME06), Paris, Centre Pompidou, 2006, pp. 134ā€“139

    Google ScholarĀ 

  28. D. Drobny, M. Weiss, J. Borchers, Saltate!: a sensor-based system to support dance beginners, Extended abstracts on Human factors in Computing Systems, in Proceedings of the CHI 09 International Conference (ACM, 2009, New York), pp. 3943ā€“3948

    Google ScholarĀ 

  29. F. Bevilacqua, L. Naugle, C. Dobrian, Music control from 3D motion capture of dance. CHI 2001 for the NIME workshop (2001)

    Google ScholarĀ 

  30. C. Dobrian, F. Bevilacqua, Gestural control of music: using the vicon 8 motion capture system, in Proceedings of the Conference on New Interfaces for Musical Expression (NIME), National University of Singapore, 2003, pp. 161ā€“163

    Google ScholarĀ 

  31. M. Raptis, D. Kirovski, H. Hoppe, Real-time classification of dance gestures from skeleton animation, in Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, New York, 2011, pp. 147ā€“156

    Google ScholarĀ 

  32. D.S. Alexiadis, P. Kelly, P. Daras, N.E. Oā€™Connor, T. Boubekeur, M.B. Moussa, Evaluating a dancerā€™s performance using kinect-based skeleton tracking, in Proceedings of the 19th ACM International Conference on Multimedia (New York, ACM, 2011), pp. 659ā€“662

    Google ScholarĀ 

  33. S. Essid, D.S. Alexiadis, R. Tournemenne, M. Gowing, P. Kelly, D.S. Monaghan et al., An advanced virtual dance performance evaluator, in Proceedings of the 37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Kyoto, 2012, pp. 2269ā€“2272

    Google ScholarĀ 

  34. G. Alankus, A.A. Bayazit, O.B. Bayazit, Automated motion synthesis for dancing characters: motion capture and retrieval. Comput. Anim. Virtual Worlds 16(3ā€“4), 259ā€“271 (2005)

    ArticleĀ  Google ScholarĀ 

  35. M. Brand, A. Hertzmann, Style machines, in Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH 2000) (ACM Press, 2000), pp. 183ā€“192

    Google ScholarĀ 

  36. D. Bouchard, N. Badler, Semantic segmentation of motion capture using laban movement analysis, in Proceedings of the 7th International Conference on Intelligent Virtual Agents, Springer, 2007. pp. 37ā€“44

    Google ScholarĀ 

  37. K. Kahol, P. Tripathi, S. Panchanathan, Automated gesture segmentation from dance sequences, in Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition (FGR04), Seoul, 2004, pp. 883ā€“888

    Google ScholarĀ 

  38. J. James, T. Ingalls, G. Qian, L. Olsen, D. Whiteley, S. Wong et al., Movement-based interactive dance performance, in Proceedings of the 14th annual ACM International Conference on Multimedia (ACM, New York, 2006), pp. 470ā€“480

    Google ScholarĀ 

  39. A.-M. Burns, M.M. Wanderley, Visual methods for the retrieval of guitarist fingering, in Proceedings of the Conference on New Interfaces for Musical Expression (IRCAM-Centre, Pompidou, 2006), pp. 196ā€“199

    Google ScholarĀ 

  40. Vision par ordinateur pour la reconnaissance des gestes musicaux des doigts, Revue Francophone dā€™Informatique Musicale [Online] Available at: http://revues.mshparisnord.org/rfim/index.php?id=107. Accessed 13 July 2013

  41. D. Grunberg, Gesture Recognition for Conducting Computer Music (n.d.) [On line] Available at: http://schubert.ece.drexel.edu/research/gestureRecognition. Accessed 10 Jan 2009

  42. J. Verner, MIDI guitar synthesis yesterday, today and tomorrow, an overview of the whole fingerpicking thing. Record. Mag. 8(9), 52ā€“57 (1995)

    Google ScholarĀ 

  43. C. Traube, An interdisciplinary study of the timbre of the classical guitar, PhD Thesis, McGill University, 2004

    Google ScholarĀ 

  44. Y. Takegawa, T. Terada, S. Nishio, Design and implementation of a real-time fingering detection system for piano performances, in Proceedings of the International Computer Music Conference, New Orleans, 2006, pp. 67ā€“74

    Google ScholarĀ 

  45. J. MacRitchie, B. Buck, N. Bailey, Visualising musical structure through performance gesture, in Proceedings of the International Society for Music Information Retrieval Conference, Kobe, 2009, pp. 237ā€“242

    Google ScholarĀ 

  46. M. Malempre, Pour une poignee de danses, Dapo Hainaut (ed.) (2010)

    Google ScholarĀ 

  47. T. Calvert, W. Wilke, R. Ryman, I. Fox, Applications of computers to dance. IEEE Comput. Graph. Appl. 25(2), 6ā€“12 (2005)

    ArticleĀ  Google ScholarĀ 

  48. Y. Shen, X. Wu, C. Lua, H. Cheng, National Dances Protection Based on Motion Capture Technology, Chengdu, Sichuan, vol. 51 (IACSIT Press, Singapore, 2012), pp. 78ā€“81

    Google ScholarĀ 

  49. W.M. Brown, L. Cronk, K. Grochow, A. Jacobson, C.K. Liu, Z. Popovic et al., Dance reveals symmetry especially in young men. Nature 438(7071), 1148ā€“1150 (2005)

    ArticleĀ  Google ScholarĀ 

  50. D. Tardieu, X. Siebert, B. Mazzarino, R. Chessini, J. Dubois, S. Dupont, G. Varni, A. Visentin, Browsing a dance video collection: dance analysis and interface design. J. Multimodal User Interf. 4(1), 37ā€“46 (2010)

    ArticleĀ  Google ScholarĀ 

  51. J.C. Chan, H. Leung, J.K. Tang, T. Komura, A virtual reality dance training system using motion capture technology. IEEE Trans. Learn. Technol. 4(2), 187ā€“195 (2011)

    ArticleĀ  Google ScholarĀ 

  52. I. Cohen, A. Garg, T. Huang, Emotion recognition from facial expression using multilevel HMM, in Proceedings of the Neural Information Processing Systems Workshop on Affective Computing, Breckenridge, 2000

    Google ScholarĀ 

  53. F. Bourel, C. Chibelushi, A. Low, Robust facial expression recognition using a state-based model of spatially-localized facial dynamics, in Proceedings of IEEE International Conference on Automatic Face and Gesture Recognition, Washington, 2002

    Google ScholarĀ 

  54. B. Schuller, S. Reiter, R. Mueller, A. Hames, G. Rigoll, Speaker independent speech emotion recognition by ensemble classification, in Proceedings of the IEEE International Conference on Multimedia and Expo, Amsterdam, 2005, pp. 864ā€“867

    Google ScholarĀ 

  55. C. Busso, Z. Deng, S. Yildirim, M. Bulut, C. Lee, A. Kazemzadeh, S. Lee, U. Neumann, S. Narayanan, Analysis of emotional recognition using facial expressions, speech and multimodal information, in Proceedings of the International Conference on Multimodal Interfaces (ACM, New York, 2004), pp. 205ā€“211

    Google ScholarĀ 

  56. R. Picard, E. Vyzas, J. Healey, Toward machine emotional intelligence: analysis of affective physiological state. IEEE Trans. Pattern Anal. Mach. Intell. 23(10), 1175ā€“1191 (2001)

    ArticleĀ  Google ScholarĀ 

  57. F. Nasoz, C. Lisetti, K. Alvarez, N. Finkelstein, Emotion recognition from physiological signals for user modeling of affect, in Proceedings of the International Conference on User Modeling, Johnstown, 2003

    Google ScholarĀ 

  58. C. Lisetti, F. Nasoz, Using non-invasive wearable computers to recognize human emotions from physiological signals. EURASIP J. Appl. Signal Process. 11, 1672ā€“1687 (2004)

    ArticleĀ  Google ScholarĀ 

  59. D. McIntosh, A. Reichmann-Decker, P. Winkielman, J. Wilbarger, When the social mirror breaks: deficits in automatic, but not voluntary, mimicry of emotional facial expressions in autism. Dev. Sci. 9, 295ā€“302 (2006)

    ArticleĀ  Google ScholarĀ 

  60. F. Esposito, D. Malerba, G. Semeraro, O. Altamura, S. Ferilli, T. Basile, M. Berard, M. Ceci, Machine learning methods for automatically processing historical documents: from paper acquisition to XML transformation, in Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL, 04), Palo Alto, 2004, pp. 328ā€“335

    Google ScholarĀ 

  61. A. Mallik, S. Chaudhuri, H. Ghosh, Nrityakosha: preserving the intangible heritage of Indian classical dance. ACM J. Comput. Cult. Herit. 4(3), 11 (2011)

    Google ScholarĀ 

  62. M. Makridis, P. Daras, Automatic classification of archaeological pottery sherds. J. Comput. Cult. Herit. 5(4), 15 (2012)

    ArticleĀ  Google ScholarĀ 

  63. A. Karasik, A complete, automatic procedure for pottery documentation and analysis, in Proceedings of the IEEE Computer Vision and Pattern Recognition Workshops (CVPRW), San Francisco, 2010, pp. 29ā€“34

    Google ScholarĀ 

  64. S. Vrochidis, C. Doulaverakis, A. Gounaris, E. Nidelkou, L. Makris, I. Kompatsiaris, A hybrid ontology and visual-based retrieval model for cultural heritage multimedia collections. Int. J. Metadata Semant. Ontol. 3(3), 167ā€“182 (2008)

    ArticleĀ  Google ScholarĀ 

  65. M. Liggins, D.L. Hall, J. Llina, Handbook of Multisensor Data Fusion, Theory and Practice, 2nd edn. (CRC Press, Boca Raton, 2008)

    BookĀ  Google ScholarĀ 

  66. O. Punska, Bayesian approach to multisensor data fusion, PhD. Dissertation, Department of Engineering, University of Cambridge, 1999

    Google ScholarĀ 

  67. S. Nikolopoulos, C. Lakka, I. Kompatsiaris, C. Varytimidis, K. Rapantzikos, Y. Avrithis, Compound document analysis by fusing evidence across media, in Proceedings of the International Workshop on Content-Based Multimedia Indexing, Chania, 2009, pp. 175ā€“180

    Google ScholarĀ 

  68. S. Chang, D. Ellis, W. Jiang, K. Lee, A. Yanagawa, A.C. Loui, J. Luo, Largescale multimodal semantic concept detection for consumer video, in Proceedings of the International Workshop on Workshop on Multimedia Information Retrieval (MIR ā€™07), September, 2007, pp. 255ā€“264

    Google ScholarĀ 

  69. R. Huber-Mƶrk, S. Zambanini, M. Zaharieva, M. Kampel, Identification of ancient coins based on fusion of shape and local features. Mach. Vision Appl. 22(6), 983ā€“994 (2011)

    ArticleĀ  Google ScholarĀ 

  70. D. Datcu, L.J.M. Rothkrantz, Semantic Audio-Visual Data Fusion for Automatic Emotion Recognition (Euromedia, Porto, 2008)

    Google ScholarĀ 

  71. M. Koolen, J. Kamps, Searching cultural heritage data: does structure help expert searchers?, in Proceedings of RIAO ā€™10 Adaptivity, Personalization and Fusion of Heterogeneous Information, Paris, 2010, pp. 152ā€“155

    Google ScholarĀ 

  72. L. Bai, S. Lao, W. Zhang, G.J.F. Jones, A.F. Smeaton, Video semantic, content analysis framework based on ontology combined MPEG-7, in Adaptive Multimedia Retrieval: Retrieval, User, and Semantics, Lecture Notes in Computer Science, July, 2007, pp. 237ā€“250

    Google ScholarĀ 

  73. S. Dasiopoulou, V. Mezaris, I. Kompatsiaris, V.K. Papastathis, G.M. Strintzis, Knowledge-assisted semantic video object detection. IEEE Trans. Circuits Syst. Video Technol. 15(10), 1210ā€“1224 (2005) (Special Issue on Analysis and Understanding for Video Adaptation)

    ArticleĀ  Google ScholarĀ 

  74. J. Lien, T. Kanade, J. Cohn, C. Li, Automated facial expression recognition based on facs action units, in Proceedings of the 3rd IEEE Conference on Automatic Face and Gesture Recognition, Nara, 1998, pp. 390ā€“395

    Google ScholarĀ 

  75. P. Mulholland, A. Wolff, T. Collins, Z. Zdrahal, An event-based approach to describing and understanding museum narratives, in Proceedings: Detection, Representation, and Exploitation of Events in the Semantic Web Workshop in Conjunction with the International Semantic Web Conference, Bonn, 2011

    Google ScholarĀ 

  76. I. Kollia, V. Tzouvaras, N. Drosopoulos, G. Stamou, A systemic approach for effective semantic access to cultural content. Semant. Web ā€“ Interoperability, Usability Appl. 3(1), 65ā€“83 (2012)

    Google ScholarĀ 

  77. A. Gaitatzes, D. Christopoulos, M. Roussou, Reviving the past: cultural heritage meets virtual reality, in Proceedings of the 2001 Conference on Virtual Reality, Archeology, and Cultural Heritage, ACM, 2001, November, pp. 103ā€“110

    Google ScholarĀ 

  78. M. Ott, F. Pozzi, Towards a new era for cultural heritage education: discussing the role of ICT. Comput. Hum. Behav. 27(4), 1365ā€“1371 (2011)

    ArticleĀ  Google ScholarĀ 

  79. K.H. Veltman, Challenges for ICT/UCT applications in cultural heritage, in ICT and Heritage, ed. by C. Carreras (2005), online at http://www.uoc.edu/digithum/7/dt/eng/dossier.pdf

  80. J.R. Savery, T.M. Duffy, Problem-based learning: an instructional model and its constructivist framework. Educ. Technol. 35, 31ā€“38 (1995)

    Google ScholarĀ 

  81. M. Mortara, C.E. Catalano, F. Bellotti, G. Fiucci, M. Houry-Panchetti, P. Petridis, Learning cultural heritage by serious games. J. Cult. Herit. 15(3), 318ā€“325 (2014)

    ArticleĀ  Google ScholarĀ 

  82. E.F. Anderson, L. McLoughlin, F. Liarokapis, C. Peters, P. Petridis, S. de Freitas, Serious games in cultural heritage, in Proceedings of the 10th International Symposium on Virtual Reality, Archaeology and Cultural Heritage VAST, ed. by M. Ashley, F. Liarokapis. State of the Art Reports (2009)

    Google ScholarĀ 

  83. M. Ott, F. Pozzi, ICT and cultural heritage education: which added value? in Emerging Technologies and Information Systems for the Knowledge Society, ed. by Lytras et al. Lecture Notes in Computer Science, 5288 (Springer, Berlin, 2008), pp. 131ā€“138

    Google ScholarĀ 

  84. X. Rodet, Y. Potard, J.-B. Barriere, The CHANT project: from the synthesis of the singing voice to synthesis in general. Comput. Music J. 8(3), 15ā€“31 (1984)

    ArticleĀ  Google ScholarĀ 

  85. G. Berndtsson, The KTH rule system for singing synthesis. Comput. Music J. 20(1), 7691 (1996)

    ArticleĀ  Google ScholarĀ 

  86. P. Cook, Physical models for music synthesis, and a meta-controller for real time performance, in Proceedings of the International Computer Music Conference and Festival, Delphi, 1992

    Google ScholarĀ 

  87. P. Cook, Singing voice synthesis: history, current work, and future directions. Comput. Music J. 20(3), 3846 (1996)

    ArticleĀ  Google ScholarĀ 

  88. G. Bennett, X. Rodet, Synthesis of the singing voice, in Current Directions in Computer Music Research, ed. by M.V. Mathews, J.R. Pierce (MIT Press, Cambridge, 1989), pp. 19ā€“44

    Google ScholarĀ 

  89. H. Kenmochi, H. Ohshita, Vocaloidā€“commercial singing synthesizer based on sample concatenation. Presented at Interspeech 2007, Antwerp, 2007, pp. 4009ā€“40010

    Google ScholarĀ 

  90. A. Kitsikidis, K. Dimitropoulos, S. Douka, N. Grammalidis, Dance analysis using multiple kinect sensors, in International Conference on Computer Vision Theory and Applications (VISAPP), IEEE, Vol. 2, 2014, January, pp. 789ā€“795

    Google ScholarĀ 

Download references

Acknowledgements

The research leading to these results has received funding from the European Communityā€™s Seventh Framework Programme (FP7-ICT-2011-9) under grant agreement no FP7-ICT-600676 ā€˜i-Treasures: Intangible Treasuresā€”Capturing the Intangible Cultural Heritage and Learning the Rare Know-How of Living Human Treasuresā€™.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nikos Grammalidis .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

Ā© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Alivizatou-Barakou, M. et al. (2017). Intangible Cultural Heritage and New Technologies: Challenges and Opportunities for Cultural Preservation and Development. In: Ioannides, M., Magnenat-Thalmann, N., Papagiannakis, G. (eds) Mixed Reality and Gamification for Cultural Heritage. Springer, Cham. https://doi.org/10.1007/978-3-319-49607-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49607-8_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49606-1

  • Online ISBN: 978-3-319-49607-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics