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Abstract

Dance, as a visual art, carries the different emotions of dancers through its movements. In response to the problem of low accuracy in traditional emotion recognition methods for dance action emotion recognition, this study proposes a dance action emotion recognition method that integrates convolutional neural networks and long short-term memory networks. It extracts features of dance action images through convolutional neural networks, recognizes actions utilizing long short-term memory networks, and then constructs a dance action emotion recognition model. Finally, by incorporating attention mechanisms into the recognition model, the key information of dance movements is focused. The experiment showed that the recognition accuracy of the research model reached 0.9472, with a root mean square error of 0.5124, significantly better than other models. In the practical application analysis of the proposed method, the recognition accuracy of the four different emotions of happiness, fear, relaxation, and sadness in dance movements reached 98.21%, 99.24%, 97.32%, and 98.49%, and was more practical than the comparative models. The above outcomes indicate that the research method can enhance the efficiency and accuracy of dance action emotion recognition, and provide a reference for subsequent scholars to conduct research in emotion recognition.

Keywords

long short-term memory network dance movements emotion recognition attention mechanism convolutional neural network

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References

Kakuba

Poulose

Han

. Attention-based multi-learning approach for speech emotion recognition with dilated convolution. IEEE Access 2022; 10(3): 122302–122313.

Vikalwe Shakrani

Mathew Kanyangarara

Parowa

, et al. A deep learning model for face recognition in presence of mask. Acta inform Malays 2022; 6(2): 43–46.

Ngwe

Lim

Lee

, et al. PAtt-lite: lightweight patch and attention MobileNet for challenging facial expression recognition. IEEE Access 2024; 12(4): 79327–79341.

Fang

Zhang

Dai

, et al. PolSAR image classification based on complex-valued convolutional long short-term memory network. IEEE GEOSCI REMOTE S 2022; 19(8): 1–5.

Rizwan

Shabbir

Javed

, et al. Brain tumor and glioma grade classification using Gaussian convolutional neural network. IEEE Access 2022; 10(3): 29731–29740.

Thakur

Biswas

ESL

, et al. ConvAE-LSTM: convolutional autoencoder long short-term memory network for smartphone-based human activity recognition. IEEE Access 2022; 10(2): 4137–4156.

Dwijayanti

Iqbal

Suprapto

. Real-time implementation of face recognition and emotion recognition in a humanoid robot using a convolutional neural network. IEEE Access 2022; 10(3): 89876–89886.

Meng

Shou

, et al. Deep imbalanced learning for multimodal emotion recognition in conversations. IEEE Trans Artif Intell 2024; 5(12): 6472–6487.

Wang

, et al. Transformers for EEG-based emotion recognition: a hierarchical spatial information learning model. IEEE SENS J 2022; 22(5): 4359–4368.

10.

Dong

Liu

, et al. Weighted feature fusion of convolutional neural network and graph attention network for hyperspectral image classification. IEEE T IMAGE PROCESS 2022; 31(4): 1559–1572.

11.

Zhao

Liu

Zhao

, et al. Class-aware adversarial multiwavelet convolutional neural network for cross-domain fault diagnosis. IEEE T IND INFORM 2024; 20(3): 4492–4503.

12.

Griffis

Patil

Bell

, et al. Lyapunov-based long short-term memory (Lb-LSTM) neural network-based control. IEEE Control Syst Lett 2023; 7(3): 2976–2981.

13.

Lui

Liu

Xie

. A supervised bidirectional long short-term memory network for data-driven dynamic soft sensor modeling. IEEE T INSTRUM MEAS 2022; 71(5): 1–13.

14.

Zhou

Zhang

Ding

, et al. A deep long short-term memory network embedded model predictive control strategies for car-following control of connected automated vehicles in mixed traffic. IEEE T INTELL TRANSP 2024; 25(7): 8209–8220.

15.

Liu

, et al. Condition monitoring and fault detection of wind turbine driveline with the implementation of deep residual long short-term memory network. IEEE SENS J 2023; 23(12): 13360–13376.

16.

Liao

Sheng

, et al. Human activity recognition using self-powered sensors based on multilayer bidirectional long short-term memory networks. IEEE SENS J 2023; 23(18): 20633–20641.

17.

Das

Paramane

Chatterjee

, et al. Sensing incipient faults in power transformers using Bi-directional long short-term memory network. IEEE Sens Lett 2023; 7(1): 1–4.

18.

Zhao

Zhang

Yang

, et al. Dynamic traffic prediction-based energy management of connected plug-in hybrid electric vehicles with long short-term state of charge planning. IEEE T VEH TECHNOL 2023; 72(5): 5833–5846.

19.

Shen

Zhao

, et al. Industrial IoT and long short-term memory network-enabled genetic indoor-tracking for factory logistics. IEEE T IND INFORM 2022; 18(11): 7537–7548.

20.

Mateo-Sanchis

Adsuara

Piles

, et al. Interpretable long short-term memory networks for crop yield estimation. IEEE GEOSCI REMOTE S 2023; 20(3): 1–5.

21.

Khanam

Hussain

Hill

, et al. A comprehensive review of convolutional neural networks for defect detection in industrial applications. IEEE Access 2024; 12(2): 94250–94295.

22.

Liu

Zheng

, et al. Cloud knowledge capability maturity model integration and evaluation method using a cloud knowledge management system. IEEE Eng Manag Rev 2023; 51(3): 93–108.

23.

Khan

Saddik

Deriche

, et al. STT-net: simplified temporal transformer for emotion recognition. IEEE Access 2024; 12(3): 86220–86231.

24.

Tian

, et al. Intelligent wearable system with motion and emotion recognition based on digital twin technology. IEEE INTERNET THINGS 2024; 11(15): 26314–26328.

25.

Hou

Zhang

Liu

, et al. Semantic alignment network for multi-modal emotion recognition. IEEE T CIRC SYST VID 2023; 33(9): 5318–5329.

26.

Zheng

Yan

Wang

. Two birds with one stone: knowledge-embedded temporal convolutional transformer for depression detection and emotion recognition. IEEE T AFFECT COMPUT 2023; 14(4): 2595–2613.

27.

Meng

Yang

, et al. Touch gesture and emotion recognition using decomposed spatiotemporal convolutions. IEEE T INSTRUM MEAS 2022; 71(3): 1–9.

28.

Shi

Peng

Chen

, et al. Multiscale 3D-shift graph convolution network for emotion recognition from human actions. IEEE Intell Syst 2022; 37(4): 103–110.

29.

Xie

Wang

, et al. Brain emotion perception inspired EEG emotion recognition with deep reinforcement learning. IEEE T NEUR NET LEAR 2024; 35(9): 12979–12992.

30.

Chen

Wang

, et al. K-means clustering-based kernel canonical correlation analysis for multimodal emotion recognition in human–robot interaction. IEEE T IND ELECTRON 2023; 70(1): 1016–1024.

Dance movement emotion recognition integrating CNN and long short term memory networks

Abstract

Keywords

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References