PROFESSIONAL DANCE MOVEMENT GESTURE DETECTION METHOD BASED ON DEEP MIGRATION LEARNING

Hwang FuhJiun
Dance Performances,Shanghai Film Art Academy,Shanghai .China. 201203
Lin Kuo-Yi
College of Electronics and Information Engineering ,Tongji University, Shanghai, China. 201804

Abstract:

Motion recognition alludes to the identification of different articulations of human body parts used to pass on thoughts, contemplations, and feelings. It is a multidisciplinary field of study. The application fields of signal recognition, for example, dance motion location, have been quickly developing in our everyday exercises. The discovery of significant feeling from different dance positions is known as dance motion identification. Dance signal discovery research is turning out to be progressively well known across the world. There are a few applications for programmed dance signal discovery. Dance movements have convoluted stance changes, bringing about low dance development discovery precision and none of the current movement recognition frameworks consider the artist's qualities. In real life location, the property normal for artist is huge undeniable level semantic data. The primary point of this study is to talk about the expert dance development motion identification technique in light of profound relocation learning. To get familiar with the troublesome and variable artist movements, a dance development distinguishing proof framework in view of component articulation and quality mining was created. The informational collection's test and examination discoveries uncover that the calculation can effectively identify dance developments and increment their accuracy, permitting the artist's development amendment capacity to be figured it out.