# Methodology of 3D Scanning of Intangible Cultural Heritage--The Example of Lazgi Dance
## 2 Traditional Dance Studies--Literature Overview
### Visualisation and Software Solutions  
Visualisation and software solutions, such as Virtual Reality (VR), Augmented Reality (AR) and software platforms are the third type of research.  
Visualisation in the form of application of Slovak folk dances recorded by using motion capture was presented in [34]. The effectiveness of learning steps from recorded dances as well as testing the overall usability of the application were verified. The game for teaching young generations of Cypriot folk dances as a way of promoting and preserving ICH was described in [12]. It was created based on 3D motion capture data. The motion of the user was captured in real time via Kinect. The game included different Skeletal Structure, body proportions and comparing motions. Another approach to the transmission of the traditional Greek Tsamiko dance in a form of game-based learning application was described in [24]. It consisted of several exercises, aiming to teach different variations of that dance. In [7] Krebspolka dance was recorded and further 3D models were used to create a mobile AR application. It provided a new way of learning and facilitate the process of learning a folk dance. This process was verified by motion capture sessions. The effect of transcranial Direct Current Stimulation (tDCS) on motor learning was analysed. It was stated that students with received tDCS perform dancing significantly better. In [13] a mobile AR application for assisting the process of learning folk dances based on 3D data was presented. Avatar representations (of either male or female) were synchronised with the digital representation of the dance. A great advantage of this system was the possibility of simultaneously learning to dance by males and females, because the dance was performed in pairs, male participants had to learn the male part of the dance and a male avatar was shown to them during the learning phase, while female participants had to learn the female version by observing a female avatar. In [27], the authors compared the movements of two avatars taking into consideration not only posture matching (meaning the physical geometry of the avatar) but also style, including the required effort, shape and interaction of the performer with the environment. Avatars were created based on 3D motion data. The presented algorithm focused on certain body parts, like upper/lower body and left/right side, as well as the whole body. Chinese performances of the Taiko drumming and lion dance recorded by smartphone were presented in [9]. This tool proved to be appropriate to register their sound. In [2] the CHROMATA platform is presented. It enabled the safeguarding of traditional dances as a part of ICH. It included analysis for 3D pose estimation, folklore dance recognition and textual analysis. Additionally, in [26], the Tsamiko dance was the topic of research where a novel methodology for dance learning and evaluation using multi-sensor and 3D gaming technology was described. Dance practitioner movements were continuously visualised with an avatar thanks to fused input from multiple sensors. The proposed system allowed to compare the quality of the student's movements with those of an expert due to the use of motion analysis and two-level Fuzzy Inference System. In [31] a method of acquiring torso movements during the traditional Japanese dance Musume-doujouji was presented. Previous studies focused primarily on the movements of the head, hands and feet, marginalising the movement of other parts of the body. The results of research using motion capture technology showedsignificant differences in the way of movements of the torso while recording the movements of professionals and amateurs constituted the basis of learning for beginners.