Comparative Analysis of Aesthetic Emotion of Dance Movement: A Deep Learning Based Approach

Abstract

Dance is a unique art with the human body movement as the main means, but dance is not limited to the human body movement itself. Like any art, dance is the product of human social behavior and a romantic behavior of human thoughts and emotions in the virtual world. Dances with different characteristics will also reflect different aesthetics, different cultural psychology, different living styles, and emotional trajectories of different times and different nationalities. People rely on the image of dance artists to develop and inherit the profound ideological connotation and philosophy of life. Viewers may form their own diversified and unique aesthetic characteristics. In the new era, in order to better promote the development, communication, and dissemination of dance art, it is very necessary to analyze and explore the connotation and aesthetic characteristics of dance art. Only through specific movements can the value and ideological connotation of works be expressed. Therefore, this paper comparatively analyzes dance movement aesthetic emotion based on deep learning. Experimentations are performed to systematically analyze the models from various perspectives. Findings of the evaluation show that CAP and CNN are effective models that can successfully extract high-level emotional features. The method proposes and effectively selects the best models among the five standard models based on key features and is, therefore, suitable in predicting the dancer’s emotion and for the analysis of the dance movement in the future.

Research on dance teaching methods based on emotion recognition and emotion analysis

“…To improve the model's understanding of dance's sequential structure, it first uses a bi-directional design that enables it to record both past and future context while analyzing motions. This assists in recognizing nuanced sentiments that are included into the dancing expressed as equation (2).…”

“…The teacher might modify the curriculum to assist the dancer learn more than technical proficiency, however, interpersonal skills and imaginative thinking are developed through the use of real-time emotional data. Teachers can create a more holistic learning environment that enhances the connection among movement, emotion and increases students' general engagement along with the appreciation of performing arts [2]. Emotion recognition technology powered by artificial intelligence (AI) has completely altered how humans recognize and understand human emotions.…”

Problems and Countermeasures to Solve Them in the System of Dance Education in Colleges and Universities in China

“…Профессиональные танцоры уделяют внимание в первую очередь совершенству физических данных и движений, но не социально-смысловой значимости танцевального искусства и ее эмоциональной нагрузке. Такое отклонение в хореографической педагогике не всегда позволяет усвоить суть танцевального искусства как необходимого элемента традиционной культуры Китая [12].…”

IoT based Dance Movement Recognition Model based on Deep Learning Framework

“…It can significantly improve the realism of the generated actions and make them resemble those of authentic dancers. Furthermore, such models can be used in other applications like interactive gaming or robotic control [6]. The Dance Pose Builder takes a set of human-defined poses as input and then learns an efficient sequence of encoded representations by learning from the input data.…”