A Solution for Improving Data Capture Process Aimed at Collecting Azeri Dance Data: An Action Research

Introduction: The modern human is on the cutting edge of information, communication, and technology, the turning point of which is to maintain the valuable traditional and cultural data inherited from the ancestors and hand down it to the descendants. This is fulfilled via stories, dances, and activities; negligence in this regard results in loss of cultural and location-based information.Materials and Methods: In this project, Perception Neuron device (a wearable system of nonoptoelectronics MoCap group) was utilized for capturing the data of the musical movements of the body. The captured data refers to the Azerbaijan region, known as Azeri Dance in the world. The study process contained three phases of possibility of identification, capturing and maintenance of musical movements on cultural-climatic backgrounds, endeavor at utilizing these musical movements of the body in creation of melodic and rhythmic patterns, and the game side of the study containing levels, game-based learning, player progress, and skill comparison among the players. The device was attached to a female performer with the body height of ۱۶۵-۱۷۰ cm according to software’s default body size with fewer flaws in data. The captured data was musical movements of the famous folk tune called Tərəkəmə (pronounces as /Tærækæmæ/).Results: The final product of the musical movements and Azeri dance was build and presented within a ۳D room in Unity game engine. The player could move around and get closer to the performers in order to watch the dance and musical movements from different angles along with hearing the real music (perfomer danced with) syncing with the movements.Conclusion: This interdisciplinary study provided an interface for Azeri dance and rhythmic melodies using digital technology. The study can be extended to any culture from any part of the earth as well as for entertainment, medical, rehabilitation, and educational purposes.

کلیدواژه ها:

Motion capture ، Motion data ، Computer game ، Georeferencing ، Musical movements