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Speaker-independent speech emotion recognition by fusion of functional and accompanying paralanguage features

Journal of Zhejiang University-Science C(Computers and Electronics) 2013年第7期14卷 573-582页

作者： Qi-rong MAO Xiao-lei ZHAO Zheng-wei HUANG Yong-zhao ZHAN Department of Computer Science and Communication Engineering Jiangsu University

Functional paralanguage includes considerable emotion information, and it is insensitive to speaker changes. To improve the emotion recognition accuracy under the condition of speaker-independence, a fusion method combining the functional paralanguage features with the accompanying paralanguage features is proposed for the speaker-independent speech emotion recognition. Using this method, the functional paralanguages, such as laughter, cry, and sigh, are used to assist speech emotion recognition. The contributions of our work are threefold. First, one emotional speech database including six kinds of functional paralanguage and six typical emotions were recorded by our research group. Second, the functional paralanguage is put forward to recognize the speech emotions combined with the accompanying paralanguage features. Third, a fusion algorithm based on confidences and probabilities is proposed to combine the functional paralanguage features with the accompanying paralanguage features for speech emotion recognition. We evaluate the usefulness of the functional paralanguage features and the fusion algorithm in terms of precision, recall, and F1-measurement on the emotional speech database recorded by our research group. The overall recognition accuracy achieved for six emotions is over 67% in the speaker-independent condition using the functional paralanguage features.

关键词： Speech emotion recognition Speaker-independent Functional paralanguage fusion algorithm Recognition accuracy

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Fast plug-in capacitors polarity detection with morphology and SVM fusion method in automatic optical inspection system

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SIGNAL IMAGE AND VIDEO PROCESSING 2023年第5期17卷 2555-2563页

作者： He, Jiawang Jiang, Lurong Zhang, Suoming Li, Renwang Xu, Changguo Liu, Xinxia Shen, Yongjian Zhejiang Sci Tech Univ Sch Informat Sci & Engn Hangzhou 310028 Zhejiang Peoples R China Zhejiang Sci Tech Univ Sch Mech Engn Hangzhou 310028 Zhejiang Peoples R China Zhejiang Dafeng Technol Co LTD Postdoctoral Workstat Hangzhou 310018 Zhejiang Peoples R China

Defect detection is a critical element in the PCB manufacturing process. Different from surface mount PCB, the components on the plug-in PCB are usually installed manually, resulting in significant errors. We make contributions in the following two aspects: (1) a framework and measurement method of a light source and make a cheap and efficient lighting system;(2) a fusion algorithm based on machine learning and morphology for polarity detection of plug-in capacitors. The capacitor is detected using SVM and fused with the polar coordinate expansion method. The AOI system and the proposed fusion algorithm have been applied to the production line, with an accuracy of 99.73% and a missed detection rate 0.12%.

关键词： Polarity detection Automatic optical inspection Light source fusion algorithm

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Perceptual medical image fusion with internal generative mechanism

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ELECTRONICS LETTERS 2017年第17期53卷 1184-1186页

作者： Qian, Jiansheng Bao, Rong Shen, Wei Hu, Junfeng Tang, Lu Xia, Zhifang China Univ Min & Technol Xuzhou 221116 Jiangsu Peoples R China Xuzhou Univ Technol Xuzhou 221018 Jiangsu Peoples R China Xuzhou Med Univ Xuzhou 221004 Jiangsu Peoples R China State Informat Ctr P R China Beijing Peoples R China

Medical image fusion is the process of integrating two medical images with a visual enhanced single fused image, to attain a resultant image richer in information to aid medical practitioners in better diagnosis. A perceptual medical image fusion method is proposed by employing Internal Generative Mechanism. First, source images are divided into a predicted layer and a detail layer with a Bayesian prediction model. Then, the detail layer is merged with the energy of Tchebichef moments for blocks while the predicted layer is fused using the averaging strategy as activity level measurement. The fused image is finally obtained by merging coefficients in both fused layers. Experimental results prove that the proposed fusion algorithm is superior to the previously developed methods.

关键词： medical image processing image fusion image enhancement Bayes methods single photon emission computed tomography ultrasonic imaging biomedical MRI biomedical ultrasonics perceptual medical image fusion internal generative mechanism visual enhanced single fused image medical practitioners diagnosis Internal Generative Mechanism source images Bayesian prediction model Tchebichef moments activity level measurement fusion algorithm SPECT MRI CT scan ultrasonic imaging

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Research on Intraoperative Organ Motion Tracking Method Based on fusion of Inertial and Electromagnetic Navigation

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IEEE ACCESS 2021年 9卷 49069-49081页

作者： Zhang, Yongde Wang, Kairui Jiang, Jingang Tan, Qiyun Harbin Univ Sci & Technol Key Lab Adv Mfg & Intelligent Technol Harbin 150080 Peoples R China Harbin Univ Sci & Technol Intelligent Machine Inst Harbin 150080 Peoples R China

The intraoperative movement of target organs is currently a key and difficult problem that restricts clinical surgery diagnosis and treatment, especially radiotherapy. Unexpected posture changes can cause the deviation of the target area during the operation, thereby affecting the treatment effect and even causing severe complications. Therefore, it is necessary to track the movement of target organs in real-time and accurately to improve the effect and safety of the surgical treatment. This paper proposes an intraoperative organ motion tracking method based on the fusion of inertial navigation and electromagnetic navigation., which can directly measure the target organ's movement under non-invasive or minimally invasive conditions using the human natural cavity. The proposed method for identifying the magnetic field's interference state uses the extended Kalman filter to fuse the inertial measurement unit and the electromagnetic positioning information to achieve target organ movement tracking under different interference conditions. It effectively improved the real-time and robustness of intraoperative organ tracking. Simultaneously, based on the 9-axis inertial measurement unit and a 6-DOF electromagnetic positioning system, the catheter-type target organ tracker was developed, and then under the simulated electromagnetic interference environment, dynamic and static verification experiments were carried out, respectively. The maximum tracking error of displacement and attitude is 2.75 mm and 0.127 rad, respectively, under severe electromagnetic disturbance through experiments. Under non-electromagnetic interference conditions, its displacement and attitude's maximum tracking errors are 0.94 mm and 0.011 rad, respectively. The results prove that the target organ tracking method based on the fusion of inertial navigation and electromagnetic navigation is feasible. It can realize the tracking and measurement of the target organ's movement within the clinical permiss

关键词： Target tracking Electromagnetics Real-time systems Navigation Position measurement Magnetic fields Magnetic field measurement Inertial navigation target organ tracking intraoperative navigation fusion algorithm

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SWIPT Enabled Intelligent Transportation Systems With Advanced Sensing fusion

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IEEE SENSORS JOURNAL 2021年第14期21卷 15643-15650页

作者： Ji, Baofeng Chen, Zhenzhen Mumtaz, Shahid Liu, Jianghui Zhang, Yong Zhu, Jia Li, Chunguo Henan Univ Sci & Technol Sch Informat Engn Luoyang 471023 Peoples R China Chinese Acad Sci Inst Atmospher Phys LAGEO Beijing 100029 Peoples R China Univ Elect Sci & Technol China Sch Aeronaut & Astronaut Chengdu 611731 Peoples R China Inst Telecommun P-3810164 Aveiro Portugal China Mobile Tietong Henan Branch Zhengzhou 450000 Peoples R China

Internet of Things (IoT) is the connections of embedded sensing technologies that can be integrated with intelligent transportation systems (ITS), which can take advantage of the advanced sensing fusion to implement the intelligent interaction. Moreover, the environmental wireless signals was harvested and utilized to power the charging sensors, which can be used to assist and enhance the ITS and have attracted extensive attentions in industries. The simultaneous wireless information and power transfer (SWIPT) enabled ITS was designed and proposed with the advanced sensing fusion, where the sensor nodes of the source and destination were all equipped with multiple antennas and the maximum ratio transmission (MRT) precoding and maximum ratio combination (MRC) were adopted respectively in the proposed system, where the sensing nodes can be embedded into the data addressing equipment to fusion the sensing information. For the established massive sensing node transmission system, the transmission power, the number of source antennas and destination antennas were considered to fuse and optimize to obtain the maximum energy efficiency (EE) of the ITS. Since the original fusion problem was non-convex and difficult to solve, which can be transformed to convex problem via the large SNR approximation method and thereby the optimal solution of the sensing fusion problem was derived through the Lagrange algorithm and the Lambert function W. The simulation results showed that the proposed fusion algorithm can achieve remarkable EE compared with other algorithms and be utilized to the massive sensors to improve the intelligent predication and transportation for vehicle network.

关键词： Internet of Things (IoT) Intelligent transportation systems (ITS) simultaneous wireless information and power transfer (SWIPT) fusion algorithm

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Interoperability technology of sports health monitoring equipment based on multi-sensor information fusion

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2021年第1期2021卷 1-18页

作者： Zhang, Di Northeastern Univ Dept Phys Educ Shenyang 110819 Liaoning Peoples R China

Nowadays, the pace of society is accelerating, people's living standard has been greatly improved compared with the past, and we pay more and more attention to the real-time, flexibility, and intelligence of medical services. Information fusion technology is the study of how to effectively and comprehensively utilize multi-sensor information to overcome information imperfections and uncertainties. In recent years, it has become a hotspot for research, but with the development of communication technology, electronic technology, and computers, the form of information becomes complicated and diverse in science and technology such as technology. In this case, the information obtained by a single sensor is always imperfect, so multiple sensors must be used to detect the target from multiple angles. Obtaining more dimensional information about the target and fusing it to ensure the integrity and accuracy of the information helps to accurately determine the physiological health of the human body. This paper analyzes the multi-sensor information fusion technology in detail, discusses the basic principle of multi-sensor information fusion, fusion process, fusion level, architecture and general fusion algorithm, constructs a sensor information fusion technology and its application model in biomedical detection, from the application framework, control structure of multi-sensor integrated system, information fusion, etc. The current situation of multi-sensor information fusion technology is studied in several aspects. An interoperability technology of sports health monitoring equipment based on multi-sensor information fusion is constructed. The experimental results show that the experimental efficiency is improved by 20% after using the application model in this paper, which has certain practicability.

关键词： Sensor information fusion technology Biomedical detection fusion algorithm Multi-sensor integrated system Biological testing

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A Saliency Map fusion Method Based on Weighted DS Evidence Theory

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IEEE ACCESS 2018年 6卷 27346-27355页

作者： Chen, Bing-Cai Tao, Xin Yang, Man-Rou Yu, Chao Pan, Wei-Min Leung, Victor C. M. Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China Xinjiang Normal Univ Sch Comp Sci & Technol Urumqi 830054 Peoples R China Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

In this paper, we propose a weighted Dempster-Shafer (DS) evidence theory-based fusion algorithm to take advantages of state-of-the-art salient object detection methods. First, we define the mass function value for each saliency detection method to be fused at the pixel level, based on which we further calculate the similarity coefficient and similarity matrix. The credibility of each saliency detection method will be computed by considering to what degree it is supported by other saliency detection methods. Second, using the credibility of each image saliency detection method as the weight, we compute the weighted mass function value of each method and get a saliency map. Third, we use the synthetic rules of DS evidence theory to fuse the weighted mass function values and get the other saliency map. The final saliency map will be obtained by fusing the aforementioned two saliency maps. Extensive experiments on three publicly available benchmark datasets demonstrate the superiority of the proposed weighted DS evidence theory-based fusion model against each individual saliency detection algorithm in terms of three evaluation metrics of precision-recall rate, F-measure, and average absolute error. The saliency map after fusion utilizing weighted DS evidence theory is closer to the ground-truth map.

关键词： Salient object detection DS evidence theory fusion algorithm mass function pixel level

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A fusion method for robust face tracking

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MULTIMEDIA TOOLS AND APPLICATIONS 2016年第19期75卷 11801-11813页

作者： Jiang, Xiaodong Yu, Hui Lu, Yang Liu, Honghai Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Dong Nanhu Rd 3888 Changchun 130033 Jilin Peoples R China Univ Portsmouth Portsmouth Hants England Univ Portsmouth Sch Comp Portsmouth Hants England Univ Portsmouth Intelligent Syst & Biomed Robot Grp ISR Portsmouth Hants England Heilongjiang Bayi Agr Univ Daqing Heilongjiang Peoples R China

Face tracking often encounters drifting problems, especially when a significant face appearance variation occurs. Many trackers suffer from the difficulty of facial feature extraction during a wide range of face turning, occlusion, and even invisibleness. In this paper, we propose a novel and efficient fusion strategy for robust face tracking. A Supervised Descent Method (SDM) and a Compressive Tracking method (CT) are employed at the same time. SDM is used to correct drifting errors of CT continuously during frontal face tracking. However, when the face orientation changes to the angle orthogonal to the view line, it results in tracking failure for the SDM method. CT is then adopted to keep the face region being tracked until SDM detects and tracks the face again. In the experiments, we test the proposed method for real-time tracking using several challenging sequences from recent literatures. The fusion strategy has achieved encouraging performance in terms of both efficiency and reliability.

关键词： fusion algorithm Human face tracking Compressive tracking Supervised descend method

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A Kalman-filter-based fusion method for accurate urban localisation

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IET COMMUNICATIONS 2021年第5期15卷 653-663页

作者： Alfakih, Marwan Keche, Mokhtar Benoudnine, Hadjira Univ Sci & Technol Oran Mohamed Boudiaf Dept Elect Signals & Images Lab BP 1505 El Mnouer 31000 Oran Algeria Univ Abdelhamid Ibn Badis Fac Sci & Technol Elect & Elect Dept Mostaganem Algeria

The outage and degradation of the global navigation satellite system (GNSS) signals caused by the multipath phenomena reduce the location accuracy of these systems in urban environment. Hence, integrating an additional localisation technology with the GNSS, so that each technology complements the weakness of the other one, is an efficient solution to improve this accuracy. The widespread availability of the Wi-Fi technology makes it the most appropriate additional technology. In this work, a fusion algorithm based on a Kalman filter is used to integrate the GPS localisation with Wi-Fi fingerprinting localisation in urban environment. The fusion algorithm uses the positions delivered by these two systems to achieve an accurate estimation of the mobile position. The experimental results show that the performance of the proposed fusion method is more accurate than those of the individual methods and other fusion methods from the literature.

关键词： Computer vision and image processing techniques Kalman-filter-based fusion method location accuracy Radionavigation and direction finding individual methods urban environment Wi-Fi technology GPS localisation accurate urban localisation image fusion Mobile radio systems Optical, image and video signal processing widespread availability Computer communications global navigation satellite system signals satellite navigation fusion algorithm indoor radio wireless LAN Kalman filters additional localisation technology GNSS degradation Global Positioning System appropriate additional technology sensor fusion outage Wi-Fi fingerprinting localisation Kalman filter multipath phenomena

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Heterogeneous sensor fusion based on Copula theory and importance sampling

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IET RADAR SONAR AND NAVIGATION 2019年第11期13卷 1943-1950页

作者： Lu, Kelin Sun, Changyin Fu, Qien Zhu, Qian Southeast Univ Sch Automat Nanjing Jiangsu Peoples R China Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing Jiangsu Peoples R China China Acad Launch Vehicle Technol Beijing Peoples R China

This study deals with the problem of heterogeneous sensor fusion based on Copula theory and importance sampling. The proposed fusion algorithm is grounded on Copula statistical modelling and Bayesian probabilistic theory. The distinctive advantage of this Copula-based methodology is that it formulates the internal dependency between the local sensors' data, which is usually unknown but essential for accurate track fusion. To this end, a joint distribution of the local sensors' observations is constructed based on Copula functions, and the corresponding fusion rule is derived with a specific correlation term. In addition, a Monte-Carlo importance sampling technique is adopted to improve the computational efficiency by drawing less random samples from the local estimates to be fused. After that, a procedure of Kernel density estimation is applied to learn a Gaussian approximation of the fused density. In the end, extensive Monte-Carlo simulations are conducted to evaluate the proposed sensor fusion method in a distributed target-tracking scenario.

关键词： Monte Carlo methods Bayes methods sensor fusion image fusion target tracking importance sampling statistical analysis Copula statistical modelling fusion algorithm heterogeneous sensor fusion sensor fusion method random samples Monte-Carlo importance sampling technique corresponding fusion rule Copula functions accurate track fusion local sensors Copula-based methodology Bayesian probabilistic theory

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