Methodology of 3D Scanning of Intangible Cultural Heritage-The Example of Lazgi Dance

被引:18
作者
Skublewska-Paszkowska, Maria [1 ]
Powroznik, Pawel [1 ]
Smolka, Jakub [1 ]
Milosz, Marek [1 ]
Lukasik, Edyta [1 ]
Mukhamedova, Dilbar [2 ]
Milosz, Elzbieta [1 ]
机构
[1] Lublin Univ Technol, Dept Comp Sci, Nadbystrzycka 36B, PL-20618 Lublin, Poland
[2] Natl Univ Uzbekistan, Dept Psychol, VUZ Gorodok, Tashkent 700174, Uzbekistan
来源
APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 23期
关键词
dance scanning; dance capturing methodology; motion capture; Lazgi dance;
D O I
10.3390/app112311568
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Traditional dance is one of the key elements of Intangible Culture Heritage (ICH). Many scientific papers concern analysis of dance sequences, classification and recognition of movements, making ICH data public, creating and visualising 3D models or software solutions for learning folklore dances. These works make it possible to preserve this disappearing art. The aim of this article is to propose a methodology for scanning folklore dances. The methodology was developed on the basis of capturing 3D data via an optical motion capture system with a full body Plug-in Gait model that allows for kinematic and kinetic analysis of motion sequences. An additional element of this research was the development of a hand model with which it is possible to precisely analyse the fingers, which play a significant role in many dances. The present methodology was verified on the basis of the Lazgi dance, included in the UNESCO ICH list. The obtained results of movement biomechanics for the dance sequence and the angles of the fingers indicate that it is universal and can be applied to dances that involve the upper and lower body parts, including hand movements.
引用
收藏
页数:17
相关论文
共 40 条
[1]   Digital Dance Ethnography: Organizing Large Dance Collections [J].
Aristidou, Andreas ;
Shamir, Ariel ;
Chrysanthou, Yiorgos .
ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE, 2019, 12 (04)
[2]   Folk Dance Evaluation Using Laban Movement Analysis [J].
Aristidou, Andreas ;
Stavrakis, Efstathios ;
Charalambous, Panayiotis ;
Chrysanthou, Yiorgos ;
Himona, Stephania Loizidou .
ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE, 2015, 8 (04)
[3]   A Virtual Reality Dance Training System Using Motion Capture Technology [J].
Chan, Jacky C. P. ;
Leung, Howard ;
Tang, Jeff K. T. ;
Komura, Taku .
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 2011, 4 (02) :187-195
[4]   Measurements of wrist and finger postures: A comparison of goniometric and motion capture techniques [J].
Cook, James R. ;
Baker, Nancy A. ;
Cham, Rakie ;
Hale, Erin ;
Redfern, Mark S. .
JOURNAL OF APPLIED BIOMECHANICS, 2007, 23 (01) :70-78
[5]  
Douka S., 2021, ADV INTELL SYST COMP, V1231, P366
[6]   Transforming Intangible Folkloric Performing Arts into Tangible Choreographic Digital Objects: The Terpsichore Approach [J].
Doulamis, Anastasios ;
Voulodimos, Athanasios ;
Doulamis, Nikolaos ;
Soile, Sofia ;
Lampropoulos, Anastasios .
PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 5, 2017, :451-460
[7]   Dancelets Mining for Video Recommendation Based on Dance Styles [J].
Han, Tingting ;
Yao, Hongxun ;
Xu, Chenliang ;
Sun, Xiaoshuai ;
Zhang, Yanhao ;
Corso, Jason J. .
IEEE TRANSACTIONS ON MULTIMEDIA, 2017, 19 (04) :712-724
[8]   The Biomechanics of Character Types in Java']Javanese Dance [J].
Hernandez-Barraza, Luis ;
Yeow, Chen-Hua ;
Varela, Miguel Escobar .
JOURNAL OF DANCE MEDICINE & SCIENCE, 2019, 23 (03) :104-111
[9]   An Enhanced Deep Convolutional Neural Network for Classifying Indian Classical Dance Forms [J].
Jain, Nikita ;
Bansal, Vibhuti ;
Virmani, Deepali ;
Gupta, Vedika ;
Salas-Morera, Lorenzo ;
Garcia-Hernandez, Laura .
APPLIED SCIENCES-BASEL, 2021, 11 (14)
[10]  
Kico I., 2019, ADV INTELL SYST COMP, V917, P245