Computer Engineering and Applications ›› 2023, Vol. 59 ›› Issue (23): 1-14.DOI: 10.3778/j.issn.1002-8331.2303-0254
• Research Hotspots and Reviews • Previous Articles Next Articles
JIN Yelei, Gulanbaier Tuerhong, Mairidan Wushouer
Online:
2023-12-01
Published:
2023-12-01
金叶磊,古兰拜尔·吐尔洪,买日旦·吾守尔
JIN Yelei, Gulanbaier Tuerhong, Mairidan Wushouer. Review of Multimodal Sensor Data Fusion in Sentiment Analysis[J]. Computer Engineering and Applications, 2023, 59(23): 1-14.
金叶磊, 古兰拜尔·吐尔洪, 买日旦·吾守尔. 情感分析中的多传感器数据融合研究综述[J]. 计算机工程与应用, 2023, 59(23): 1-14.
Add to citation manager EndNote|Ris|BibTeX
URL: http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2303-0254
[1] HALL D L,LLINAS J.An introduction to multisensor data fusion[J].Proceedings of the IEEE,1997,85(1):6-23. [2] CALVERT G A,THESEN T.Multisensory integration:methodological approaches and emerging principles in the human brain[J].Journal of Physiology-Paris,2004,98(1/2/3):191-205. [3] MACALUSO E,DRIVER J.Multisensory spatial interactions:a window onto functional integration in the human brain[J].Trends in Neurosciences,2005,28(5):264-271. [4] HACKETT J K,SHAH M.Multi-sensor fusion:a perspective[C]//Proceedings of the IEEE International Conference on Robotics and Automation,1990:1324-1330. [5] ARD R W,HEALEY J.Affective wearables[J].Personal Technologies,1997,1(4):231-240. [6] GRAVINA R,ALINIA P,GHASEMZADEH H,et al.Multi-sensor fusion in body sensor networks:state-of-the-art and research challenges[J].Information Fusion,2017,35:68-80. [7] KIRSCHSTEIN T,K?HLING R.What is the source of the EEG?[J].Clinical EEG and Neuroscience,2009,40(3):146-149. [8] MALIK M,CAMM A J.Heart rate variability[J].Clinical Cardiology,1990,13(8):570-576. [9] SHARMA M,KACKER S,SHARMA M.A brief introduction and review on galvanic skin response[J].Int J Med Res Prof,2016,2(6):13-17. [10] SWEENEY H L,HAMMERS D W.Muscle contraction[J].Cold Spring Harbor Perspectives in Biology,2018,10(2):023200. [11] BOS D O.EEG-based emotion recognition[J].The Influence of Visual and Auditory Stimuli,2006,56(3):1-17. [12] APPELHANS B M,LUECKEN L J.Heart rate variability as an index of regulated emotional responding[J].Review of General Psychology,2006,10(3):229-240. [13] LIM J Z,MOUNTSTEPHENS J,TEO J.Emotion recognition using eye-tracking:taxonomy,review and current challenges[J].Sensors,2020,20(8):2384. [14] NICHOLSON D,LLOYD C M,JULIER S J,et al.Scalable distributed data fusion[C]//Proceedings of the Fifth International Conference on Information Fusion,2002:630-635. [15] CASTANEDO F.A review of data fusion techniques[J].The Scientific World Journal,2013:704504. [16] 郝凯.基于多传感器数据融合的姿态识别算法的研究与实现[D].吉林:吉林大学,2020. HAO K.Research and implementation of attitude recognition algorithm based on multi-sensor data fusion[D].Jilin:Jilin University,2020. [17] 杨露菁,余华.多源信息融合理论与应用[M].北京:北京邮电大学出版社,2006. YANG L J,YU H.Theory and application of multi-source information fusion[M].Beijing University of Posts and Telecommunications Press,2006. [18] TER BRAAK C J F,LOOMAN C W N.Weighted averaging,logistic regression and the Gaussian response model[J].Vegetatio,1986,65(1):3-11. [19] ZHAO X,LUO Q,HAN B.Survey on robot multi-sensor information fusion technology[C]//2008 7th World Congress on Intelligent Control and Automation,2008:5019-5023. [20] SHAFER G.Dempster-shafer theory[J].Encyclopedia of Artificial Intelligence,1992,1:330-331. [21] 易建政,汪金军,张俊坤,等.D-S证据理论在信息融合中的应用研究[J].国外电子测量技术,2010(12):31-34. YI J Z,WANG J J,ZHANG J K,et al.Application research on D-S evidence theory in data fusion[J].Foreign Electronic Measurement Technology,2010(12):31-34. [22] YANG M S.A survey of fuzzy clustering[J].Mathematical and Computer Modelling,1993,18(11):1-16. [23] 毛健,赵红东,姚婧婧.人工神经网络的发展及应用[J].电子设计工程,2011,19(24):62-65. MAO J,ZHAO H D,YAO J J.Application and prospect of artificial neural network[J].Electronic Design Engineering,2011,19(24):62-65. [24] 张红,程传祺,徐志刚,等.基于深度学习的数据融合方法研究综述[J].计算机工程与应用,2020,56(24):1-11. ZHANG H,CHENG C Q,XU Z G,et al.Survey of data fusion based on deep learning[J].Computer Engineering and Applications,2020,56(24):1-11. [25] LIU Y,ZHANG C,CHENG J,et al.A multi-scale data fusion framework for bone age assessment with convolutional neural networks[J].Computers in Biology and Medicine,2019,108:161-173. [26] WU J,HU K,CHENG Y,et al.Data-driven remaining useful life prediction via multiple sensor signals and deep long short-term memory neural network[J].ISA Transactions,2019,97:241-250. [27] LI S,WANG H,SONG L,et al.An adaptive data fusion strategy for fault diagnosis based on the convolutional neural network[J].Measurement,2020,165:108122. [28] 林加润.基于多传感器数据融合的攻击检测与意图识别方法研究[D].北京:国防科学技术大学,2010. LIN J R.Research on attack detection and intent recognition based on multi-sensor data fusion[D].Beijing:National University of Defense Technology,2010. [29] 黄鹍.基于智能技术的多源信息融合理论与应用研究[D].南京:东南大学,2004. HUANG K,Research on the theory and applications of multi-source[D].Nanjing:Southeast University,2004. [30] 李娟,李甦,李斯娜,等.多传感器数据融合技术综述[J].云南大学学报(自然科学版),2008,30(S2):241-246. LI J,LI S,LI S N,et al.A survey of multi-sensor data fusion technology[J].Journal of Yunnan Universitt,2008,30(S2):241-246. [31] 张丽霞,曾广平,宣兆成.多源图像融合方法的研究综述[J].计算机工程与科学,2022,44(2):321-334. ZHANG L X,ZENG G P,XUAN Z C.A survey of fusion methods for multi-source image[J].Computer Engineering & Science,2022,44(2):321-334. [32] SWAIN M,ROUTRAY A,KABISATPATHY P.Databases,features and classifiers for speech emotion recognition:a review[J].International Journal of Speech Technology,2018,21:93-120. [33] MCFEE B,RAFFEL C,LIANG D,et al.Librosa:audio and music signal analysis in Python[C]//Proceedings of the 14th Python in Science Conference,2015:18-25. [34] EYBEN F,SCHULLER B.Opensmile:the munich open-source large-scale multimedia feature extractor[J].ACM SIG Multimedia Records,2015,6(4):4-13. [35] ZHANG S,ZHANG S,HUANG T,et al.Speech emotion recognition using deep convolutional neural network and discriminant temporal pyramid matching[J].IEEE Transactions on Multimedia,2017,20(6):1576-1590. [36] SAJJAD M,KWON S.Clustering-based speech emotion recognition by incorporating learned features and deep BiLSTM[J].IEEE Access,2020,8:79861-79875. [37] MIRSAMADI S,BARSOUM E,ZHANG C.Automatic speech emotion recognition using recurrent neural networks with local attention[C]//IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP),LA,USA,2017:2227-2231. [38] SARMA M,GHAHREMANI P,POVEY D,et al.Emotion identification from raw speech signals using DNNs[C]//International Speech Communication Association,Hyderabad,India,2018:3097-3101. [39] ZHAO J,MAO X,CHEN L.Speech emotion recognition using deep 1D&2D CNN LSTM networks[J].Biomedical Signal Processing and Control,2019,47:312-323. [40] SENGUPTA A,YE Y,WANG R,et al.Going deeper in spiking neural networks:VGG and residual archi-tectures[J].Frontiers in Neuroscience,2019:02627. [41] TARG S,ALMEIDA D,LYMAN K.Resnet in resnet:generalizing residual architectures[J].arXiv:1603.08029,2016. [42] SZEGEDY C,VANHOUCKE V,IOFFE S,et al.Rethinking the inception architecture for computer vision[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2016:2818-2826. [43] HE K,ZHANG X,REN S,et al.Deep residual learning for image recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2016:770-778. [44] VAN GENT P.Emotion recognition using facial land-marks python DLib and OpenCV[J].A Tech Blog About Fun Things with Python Embedded Electronics,2016. [45] KUSUMA G P,JONATHAN J,LIM A P.Emotion recognition on FER-2013 face images using fine-tuned VGG-16[J].Advances in Science,Technology and Engineering Systems Journal,2020,5(6):315-322. [46] LI B,LIMA D.Facial expression recognition via ResNet-50[J].International Journal of Cognitive Computing in Engineering,2021,2:57-64. [47] WANG S,JI Q.Video affective content analysis:a survey of state-of-the-art methods[J].IEEE Transactions on Affective Computing,2015,6(4):410-430. [48] COHEN I,SEBE N,GARG A,et al.Facial expression recognition from video sequences[C]//Proceedings of the IEEE International Conference on Multimedia and Expo,2002,2:121-124. [49] ZHANG S,PAN X,CUI Y,et al.Learning affective video features for facial expression recognition via hybrid deep learning[J].IEEE Access,2019,7:32297-32304. [50] LIU M,SHAN S,WANG R,et al.Learning expressionlets on spatio-temporal manifold for dynamic facial expression recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2014:1749-1756. [51] LIU Y,FENG C,YUAN X,et al.Clip-aware expressive feature learning for video-based facial expression recognition[J].Information Sciences,2022,598:182-195. [52] ZHANG Y,JIN R,ZHOU Z H.Understanding bag-of-words model:a statistical framework[J].International Journal of Machine Learning and Cybernetics,2010,1(1/2/3/4):43-52. [53] ROELLEKE T,WANG J.TF-IDF uncovered:a study of theories and probabilities[C]//Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval,2008:435-442. [54] LI Y,YANG T.Word embedding for understanding natural language:a survey[J].Guide to Big Data Applications,2018:83-104. [55] DOS SANTOS C,GATTI M.Deep convolutional neural networks for sentiment analysis of short texts[C]//Proceedings of COLING 2014,the 25th International Conference on Computational Linguistics:Technical Papers,2014:69-78. [56] KENTON J D M W C,TOUTANOVA L K.BERT:pre-training of deep bidirectional transformers for language understanding[C]//Proceedings of NAACL-HLT,2019:4171-4186. [57] RAFFEL C,SHAZEER N,ROBERTS A,et al.Exploring the limits of transfer learning with a unified text-to-text transformer[J].The Journal of Machine Learning Research,2020,21(1):5485-5551. [58] YANG Z,YANG D,DYER C,et al.Hierarchical attention networks for document classification[C]//Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2016:1480-1489. [59] HAZARIKA D,GORANTLA S,PORIA S,et al.Self-attentive feature-level fusion for multimodal emotion detection[C]//2018 IEEE Conference on Multimedia Information Processing and Retrieval(MIPR),2018:196-201. [60] ELFAIK H.Leveraging feature-level fusion representa-tions and attentional bidirectional RNN-CNN deep models for Arabic affect analysis on Twitter[J].Journal of King Saud University-Computer and Information Sciences,2023,35(1):462-482. [61] PAPPAGARI R,WANG T,VILLALBA J,et al.X-vectors meet emotions:a study on dependencies between emotion and speaker recognition[C]//IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP),Barcelona,Spain,2020:7169-7173. [62] ABDULLAH S M S A,AMEEN S Y A,SADEEQ M A M,et al.Multimodal emotion recognition using deep learning[J].Journal of Applied Science and Technology Trends,2021,2(2):52-58. [63] LIU Z,SHEN Y,LAKSHMINARASIMHAN V B,et al.Efficient low-rank multimodal fusion with modality-specific factors[J].arXiv:1806.00064,2018. [64] ZADEH A,CHEN M,PORIA S,et al.Tensor fusion network for multimodal sentiment analysis[J].arXiv:1707. 07250,2017. [65] SAHOO S,ROUTRAY A.Emotion recognition from audio-visual data using rule based decision level fusion[C]//2016 IEEE Students’ Technology Symposium(TechSym),2016:7-12. [66] XIE J,XU X,SHU L.WT feature based emotion recognition from multi-channel physiological signals with decision fusion[C]//2018 First Asian Conference on Affective Computing and Intelligent Interaction(ACII Asia),2018:1-6. [67] ZHANG Q,ZHANG H,ZHOU K,et al.Developing a physiological signal-based,mean threshold and decision-level fusion algorithm(PMD) for emotion recognition[J].Tsinghua Science and Technology,2023,28(4):673-685. [68] YAN M S,DENG Z,HE B W,et al.Emotion classification with multichannel physiological signals using hybrid feature and adaptive decision fusion[J].Biomedical Signal Processing and Control,2022,71:103235. [69] ZADEH A,LIANG P P,MAZUMDER N,et al.Memory fusion network for multi-view sequential learning[C]//Proceedings of the AAAI Conference on Artificial Intelligence,2018. [70] ZHANG Z,CHEN K,WANG R,et al.Neural machine translation with universal visual representation[C]//International Conference on Learning Representations,2020. [71] 韩天翊,林荣恒.一种基于决策层融合的多模态情感识别方法[J].南京师范大学学报(工程技术版),2022,22(2):35-40. HAN T Y,LIN R H.A multimodal emotion recognition method based on decision level fusion[J].Journal of Nanjing Normal University(Engineering and Technology Edition),2022,22(2):35-40. [72] ZHANG S,ZHANG S,HUANG T,et al.Learning affec-tive features with a hybrid deep model for audio-visual emotion recognition[J].IEEE Transactions on Circuits & Systems for Video Technology,2017,28(10):673-685. [73] ZHENG W,LIU W,LU Y,et al.Emotionmeter:a mul timodal framework for recognizing human emotions[J].IEEE Transactions on Cybernetics,2018,49(3):1110-1122. [74] MIDDYA A I,NAG B,ROY S.Deep learning based multi-modal emotion recognition using model-level fusion of audio-visual modalities[J].Knowledge-Based Systems,2022,244:108580. [75] XU H,ZHANG H,HAN K,et al.Learning alignment for multimodal emotion recognition from speech[J].arXiv:1909.05645,2019. [76] ZHENG W L,LU B L.Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks[J].IEEE Transactions on Autonomous Mental Development,2015,7(3):162-175. [77] NOJAVANASGHARI B,BALTRU?AITIS T,HUGHES C E,et al.Emoreact:a multimodal approach and dataset for recognizing emotional responses in children[C]//Proceedings of the 18th ACM International Conference on Multimodal Interaction,2016:137-144. [78] ZHANG Y,LAI G,ZHANG M,et al.Explicit factor models for explainable recommendation based on phrase-level sentiment analysis[C]//Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval,2014:83-92. [79] PORIA S,HAZARIKA D,MAJUMDER N,et al.Meld:a multimodal multi-party dataset for emotion recognition in conversations[J].arXiv:1810.02508,2018. [80] JACKSON P,HAQ S.Surrey audio-visual expressed emotion(SAVEE) database[J].University of Surrey:guild-ford,UK,2014. [81] LIVINGSTONE S R,RUSSO F A.The ryerson au-dio-visual data-base of emotional speech and song(RAVDESS):a dynamic,multimodal set of facial and vocal expressions in north American english[J].PloS One,2018,13(5):e0196391. [82] AL-AZANI S,EL-ALFY E S M.Enhanced video analytics for sentiment analysis based on fusing textual,auditory and visual information[J].IEEE Access,2020,8:136843-136857. [83] BARROS P,CHURAMANI N,LAKOMKIN E,et al.The OMG-emotion behavior dataset[C]//2018 International Joint Conference on Neural Networks(IJCNN),2018:1-7. [84] YU W,XU H,MENG F,et al.CH-SIMS:a chinese multimodal sentiment analysis dataset with fine-grained annotation of modality[C]//Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics,2020:3718-3727. [85] ZADEH A A B,LIANG P P,PORIA S,et al.Multimodal language analysis in the wild:cmu-mosei dataset and interpretable dynamic fusion graph[C]//Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics,2018:2236-2246. [86] CERVELLINI P,MENEZES A G,MAGO V K.Finding trendsetters on yelp dataset[C]//2016 IEEE Symposium Series on Computational Intelligence(SSCI),2016:1-7. [87] BUSSO C,BULUT M,LEE C C,et al.IEMOCAP:interactive emotional dyadic motion capture database[J].Language Resources and Evaluation,2008,42:335-359. [88] RINGEVAL F,SONDEREGGER A,SAUER J,et al.Introducing the RECOLA multimodal corpus of remote collaborative and affective interactions[C]//2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition(FG),2013:1-8. [89] YANG Q,PENG G,NGUYEN D T,et al.A multimodal data set for evaluating continuous authentication performance in smartphones[C]//Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems,2014:358-359. [90] PLACIDI G,DI GIAMBERARDINO P,PETRACCA A,et al.Classification of Emotional Signals from the DEAP dataset[C]//Proceedings of the Neurotechnix,2016:15-21. [91] BILAKHIA S,PETRIDIS S,NIJHOLT A,et al.The MAHNOB Mimicry Database:a database of naturalistic human interactions[J].Pattern Recognition Letters,2015,66:52-61. |
[1] | LIU Hualing, CHEN Shanghui, QIAO Liang, LIU Yaxin. Multimodal False News Detection Based on Fusion Attention Mechanism [J]. Computer Engineering and Applications, 2023, 59(9): 95-103. |
[2] | CAI Zhengyi, ZHAO Jieyu, ZHU Feng. Single-Stage Object Detection with Fusion of Point Cloud and Image Feature [J]. Computer Engineering and Applications, 2023, 59(9): 140-149. |
[3] | LUO Huilan, CHEN Han. Spatial-Temporal Convolutional Attention Network for Action Recognition [J]. Computer Engineering and Applications, 2023, 59(9): 150-158. |
[4] | XIE Chunhui, WU Jinming, XU Huaiyu. Small Object Detection Algorithm Based on Improved YOLOv5 in UAV Image [J]. Computer Engineering and Applications, 2023, 59(9): 198-206. |
[5] | XU Zhijing, LIU Xia. Bimodal Emotion Recognition Model Based on Cascaded Two Channel Phased Fusion [J]. Computer Engineering and Applications, 2023, 59(8): 127-137. |
[6] | GUO Pingxiu, LI Qinan, YANG Zhongpeng. Image Enhancement and Improved Marine Biological Image Detection Algorithm [J]. Computer Engineering and Applications, 2023, 59(8): 208-216. |
[7] | TIAN Xuewei, WANG Jiali, CHEN Ming, DU Shouqing. Improved SegFormer Network Based Method for Semantic Segmentation of Remote Sensing Images [J]. Computer Engineering and Applications, 2023, 59(8): 217-226. |
[8] | ZHANG Zhaoyang, ZHANG Shang, WANG Hengtao, RAN Xiukang. Multi-Head Attention Detection of Small Targets in Remote Sensing at Multiple Scales [J]. Computer Engineering and Applications, 2023, 59(8): 227-238. |
[9] | LI Shaohua, GUO He, FENG Jingying, HE Wei. Optimal Maintenance Decision Model for Sensor Network [J]. Computer Engineering and Applications, 2023, 59(8): 315-321. |
[10] | WU Haoyuan, XIONG Xin, MIN Weidong, ZHAO Haoyu, WANG Wenxiang. Action Recognition Method Based on Multi-Level Feature Fusion and Temporal Extension [J]. Computer Engineering and Applications, 2023, 59(7): 134-142. |
[11] | HAN Zonghuan, LIU Mingguo, LI Shen, CHEN Lijia, TIAN Min, LAN Tianxiang, LIANG Qian. Unsupervised Segmentation Algorithm Based on Multi-Scale Feature Fusion and Novel Discriminator [J]. Computer Engineering and Applications, 2023, 59(7): 152-162. |
[12] | LUO Penlin, FANG Yanhong, LI Xin, LI Xue. Dual-Modal Feature Fusion Semantic Segmentation of RGB-D [J]. Computer Engineering and Applications, 2023, 59(7): 222-231. |
[13] | CHAI Yan, SUN Xiaoxiao, REN Sheng. Chaotic Sparrow Search Algorithm Based on Multi-Directional Learning [J]. Computer Engineering and Applications, 2023, 59(6): 81-91. |
[14] | LI Yu, HAN Xiaohong, ZHANG Ling, ZHANG Haixuan, LI Gang. Seismic P-Wave First-Arrival Picking Model Based on Spatiotemporal Attention Mechanism [J]. Computer Engineering and Applications, 2023, 59(6): 113-124. |
[15] | ZHANG Haoyu, ZHANG De. Cascading Attention Visual Question Answering Model Based on Graph Structure [J]. Computer Engineering and Applications, 2023, 59(6): 155-161. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||