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面部表情识别技术在智能家居中的应用研究
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Abstract:
随着智能家居技术的发展，情绪识别(FER)技术的应用日益广泛，成为提升人机交互体验和个性化服务的重要工具。本文通过综述现有的FER技术及其在智能家居中的应用，分析了该领域的主要研究进展，并指出了现有研究中的局限性。文章提出了对FER技术的应用进行系统性归纳和分析的新视角，特别是在情绪调节与个性化环境适配方面的潜力。通过总结不同研究的成果，本文明确了当前技术面临的挑战，并展望了未来的研究方向，包括多模态数据融合、深度学习优化以及更智能的情绪调节机制。本文的创新性在于通过对现有技术的全面分析，提出了一些尚未被充分研究的应用方向，并为未来智能家居领域的研究提供了新的视角和思路。
With the development of smart home technologies, emotion recognition (FER) has become a key tool for enhancing human-computer interaction and providing personalized services. This paper reviews the existing FER technologies and their applications in smart homes, analyzing the major research progress in the field and identifying the limitations in current studies. The paper offers a new perspective on the application of FER, particularly its potential in emotional regulation and personalized environmental adaptation. By synthesizing findings from different studies, this paper highlights the challenges facing current technologies and anticipates future research directions, including multi-modal data fusion, deep learning optimization, and more intelligent emotional regulation mechanisms. The innovation of this paper lies in its comprehensive analysis of existing technologies, proposing underexplored application directions and providing new perspectives and ideas for future research in the smart home domain.
| [1] | Ghimire, D., Park, S.H. and Kim, M.J. (2017) Facial Expression Recognition Using Local Region Specific Dense Optical Flow and LBP Features. Advanced Concepts for Intelligent Vision Systems, Antwerp, 18-21 September 2017, 28-38. https://doi.org/10.1007/978-3-319-70353-4_3 |
| [2] | Zhang, Y. and Ji, Q. (2005) Active and Dynamic Information Fusion for Facial Expression Understanding from Image Sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27, 699-714. https://doi.org/10.1109/tpami.2005.93 |
| [3] | Schuldt, C., Laptev, I. and Caputo, B. (2004) Recognizing Human Actions: A Local SVM Approach. Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004, Cambridge, 26 August 2004, 32-36. https://doi.org/10.1109/icpr.2004.1334462 |
| [4] | Zhang, Z., Lyons, M., Schuster, M., et al. (1998) Comparison between Geometry-Based and Gabor Wavelets-Based Facial Expression Recognition Using Multi-Layer Perceptron. Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition, Nara, 14-16 April 1998, 454-459. https://doi.org/10.1109/AFGR.1998.670990 |
| [5] | 徐峰, 张军平. 人脸微表情识别综述[J]. 自动化学报, 2017, 43(3): 333-348. |
| [6] | Mollahosseini, A., Chan, D. and Mahoor, H.M. (2015) Going Deeper in Facial Expression Recognition Using Deep Neural Networks. 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, 7-10 March 2016, 1-10. https://doi.org/10.1109/WACV.2016.7477450 |
| [7] | 孙晓, 潘汀, 任福继. 基于ROI-KNN卷积神经网络的面部表情识别[J]. 自动化学报, 2016, 42(6): 883-891. |
| [8] | Yim, J., Jung, H., Yoo, B., Choi, C., Park, D. and Kim, J. (2015) Rotating Your Face Using Multi-Task Deep Neural Network. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, 7-12 June 2015, 676-684. https://doi.org/10.1109/cvpr.2015.7298667 |
| [9] | Zhang, J., Kan, M., Shan, S. and Chen, X. (2016) Occlusion-Free Face Alignment: Deep Regression Networks Coupled with De-Corrupt Autoencoders. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, 27-30 June 2016, 3428-3437. https://doi.org/10.1109/cvpr.2016.373 |
| [10] | Howard, A., Sandler, M., Chen, B., Wang, W., Chen, L., Tan, M., et al. (2019) Searching for MobileNetV3. 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, 27 October-2 November 2019, 1314-1324. https://doi.org/10.1109/iccv.2019.00140 |
| [11] | Tan, M. and Quoc V. Le. (2019) EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. Proceedings of the 36th International Conference on Machine Learning, Long Beach, 9-15 June 2019, 6105-6114. |
| [12] | Katsigiannis, S. and Ramzan, N. (2018) DREAMER: A Database for Emotion Recognition through EEG and ECG Signals from Wireless Low-Cost off-the-Shelf Devices. IEEE Journal of Biomedical and Health Informatics, 22, 98-107. https://doi.org/10.1109/jbhi.2017.2688239 |
| [13] | Gamage, K.W., Sethu, V. and Ambikairajah, E. (2017) Salience Based Lexical Features for Emotion Recognition. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, 5-9 March 2017, 5830-5834. https://doi.org/10.1109/icassp.2017.7953274 |
| [14] | 徐志京, 高姗. 基于Transformer-ESIM注意力机制的多模态情绪识别[J]. 计算机工程与应用, 2022, 58(10): 132-138. |
| [15] | Akinpelu, S., Viriri, S. and Adegun, A. (2024) An Enhanced Speech Emotion Recognition Using Vision Transformer. Scientific Reports, 14, Article No. 13126. https://doi.org/10.1038/s41598-024-63776-4 |
| [16] | Zadeh, A., Zellers, R., Pincus, E. and Morency, L. (2016) Multimodal Sentiment Intensity Analysis in Videos: Facial Gestures and Verbal Messages. IEEE Intelligent Systems, 31, 82-88. https://doi.org/10.1109/mis.2016.94 |
| [17] | Wang, C. (2022) Improved Generative Adversarial Networks for Student Classroom Facial Expression Recognition. Scientific Programming, 2022, Article ID: 9471334. https://doi.org/10.1155/2022/9471334 |
| [18] | Yang, H., Ciftci, U. and Yin, L. (2018) Facial Expression Recognition by De-Expression Residue Learning. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, 18-23 June 2018, 2168-2177. https://doi.org/10.1109/cvpr.2018.00231 |
| [19] | 权学良, 曾志刚, 蒋建华, 等. 基于生理信号的情感计算研究综述[J]. 自动化学报, 2021, 47(8): 1769-1784. |
| [20] | Luo, Y., Zhang, S., Zheng, W. and Lu, B. (2018) WGAN Domain Adaptation for EEG-Based Emotion Recognition. Neural Information Processing, Siem Reap, 13-16 December 2018, 275-286. https://doi.org/10.1007/978-3-030-04221-9_25 |
| [21] | Ma, B.Q., Li, H., Zheng, W.L. and Lv, B.L. (2019) Reducing the Subject Variability of EEG Signals with Adversarial Domain Generalization. Neural Information Processing, Sydney, 12-15 December 2019, 30-42. https://doi.org/10.1007/978-3-030-36708-4_3 |
| [22] | 姚乃明, 郭清沛, 乔逢春, 等. 基于生成式对抗网络的鲁棒人脸表情识别[J]. 自动化学报, 2018, 44(5): 865-877. |
| [23] | Dosovitskiy, A., Beyer, L., Kolesnikov, A., et al. (2020) An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. arXiv: 2010.11929. |
| [24] | 陈宗楠, 金家瑞, 潘家辉. 基于Swin Transformer的四维脑电情绪识别[J]. 计算机技术与发展, 2023, 33(12): 178-184. |
| [25] | Wani, T.M., Gunawan, T.S., Qadri, S.A.A., Kartiwi, M. and Ambikairajah, E. (2021) A Comprehensive Review of Speech Emotion Recognition Systems. IEEE Access, 9, 47795-47814. https://doi.org/10.1109/access.2021.3068045 |
| [26] | 杨亚飞. 基于深度学习的自然场景下人脸表情识别方法研究[D]: [硕士学位论文]. 成都: 电子科技大学, 2023. |
| [27] | Khare, S.K., Blanes-Vidal, V., Nadimi, E.S. and Acharya, U.R. (2024) Emotion Recognition and Artificial Intelligence: A Systematic Review (2014-2023) and Research Recommendations. Information Fusion, 102, Article 102019. https://doi.org/10.1016/j.inffus.2023.102019 |
| [28] | Patil, V.K., Hadawale, O., Pawar, V.R. and Gijre, M. (2021) Emotion Linked AioT Based Cognitive Home Automation System with Sensovisual Method. 2021 IEEE Pune Section International Conference (PuneCon), Pune, 16-19 December 2021, 1-7. https://doi.org/10.1109/punecon52575.2021.9686498 |
| [29] | Wang, M., Ma, H., Wang, Y. and Sun, X. (2024) Design of Smart Home System Speech Emotion Recognition Model Based on Ensemble Deep Learning and Feature Fusion. Applied Acoustics, 218, Article 109886. https://doi.org/10.1016/j.apacoust.2024.109886 |
| [30] | Chen, M., Yang, J., Zhu, X., Wang, X., Liu, M. and Song, J. (2017) Smart Home 2.0: Innovative Smart Home System Powered by Botanical IoT and Emotion Detection. Mobile Networks and Applications, 22, 1159-1169. https://doi.org/10.1007/s11036-017-0866-1 |
| [31] | Yang, J., Qian, T., Zhang, F. and Khan, S.U. (2021) Real-Time Facial Expression Recognition Based on Edge Computing. IEEE Access, 9, 76178-76190. https://doi.org/10.1109/access.2021.3082641 |
| [32] | Zhao, S., Gholaminejad, A., Ding, G., Gao, Y., Han, J. and Keutzer, K. (2019) Personalized Emotion Recognition by Personality-Aware High-Order Learning of Physiological Signals. ACM Transactions on Multimedia Computing, Communications, and Applications, 15, 1-18. https://doi.org/10.1145/3233184 |
| [33] | Beltrán, M. and Calvo, M. (2023) A Privacy Threat Model for Identity Verification Based on Facial Recognition. Computers & Security, 132, Article 103324. https://doi.org/10.1016/j.cose.2023.103324 |
