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第35届中国控制会议

作者： Dandi Chen Siyu Xia Yuan Zhou Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Computer Science and Engineering Department University of Connecticut

ISBN: (纸本)9781509009107

Pedestrian detection has been the key point of several hot research fields,including intelligent surveillance,driving assistance,intelligent robot,*** to pedestrian appearance,multi-pose,angle of view,environment and other factors,the existing pedestrian detection algorithms still have some unsolved technical *** this paper,we focus on contour *** on traditional feature descriptors and feature selection methods,we proposed a novel oriented Chamfer distance(OCD) feature to describe pedestrian *** improves anti-interference ability of image noise using Bag of Words(BOW)model and image multi-scale ***,we conducted experimental comparisons using scale-invariant feature transform(SIFT),histogram of oriented gradient(HOG),speeded up robust feature(SURF) and OCD feature in feature extraction and parameter optimization,in Boosting and support vector machine(SVM) classification *** results demonstrate that the proposed OCD feature has great discriminant ability of pedestrian contours.

关键词： Pedestrian detection Contour feature Oriented Chamfer distance feature Support vector machine Boosting

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Speech emotion recognition based on deep belief networks and wavelet packet cepstral coefficients

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International Journal of Simulation: systems, Science and Technology 2016年第28期17卷 28.1-28.5页

作者： Huang, Yongming Wu, Ao Zhang, Guobao Li, Yue School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

A wavelet packet based adaptive filter-bank construction combined with Deep Belief Network(DBN) feature learning method is proposed for speech signal processing in this paper. On this basis, a set of acoustic features are extracted for speech emotion recognition, namely Coiflet Wavelet Packet Cepstral Coefficients (CWPCC). CWPCC extends the conventional Mel-Frequency Cepstral Coefficients (MFCC) by adapting the filter-bank structure according to the decision task. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre-trained layer by layer and then fine-tuned using back propagation algorithm. The well-trained deep neural networks are capable of modeling complex and non-linear features of input training data and can better predict the probability distribution over classification labels. Speech emotion recognition system is constructed with the feature set, DBNs feature learning structure and Support Vector Machine as classifier. Experimental results on Berlin emotional speech database show that the Coiflet Wavelet Packet is more suitable in speech emotion recognition than other acoustics features and proposed DBNs feature learning structure combined with CWPCC improve emotion recognition performance over the conventional emotion recognition method. © 2016, UK Simulation Society. All rights reserved.

关键词： Filter banks

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An algorithm for assembly job shop scheduling problem

An algorithm for assembly job shop scheduling problem

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2016 2nd International Conference on Electronics,Network and Computer engineering(ICENCE 2016)

作者： Xiao-Qin Wan Hong-Sen Yan School of Automation Southeast University MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University

ISBN: (纸本)9781510830073

The problem of assembly job shop scheduling(AJSS) is studied with the objective of minimizing the weighted sum of earliness and tardiness penalties. An insertion search algorithm is proposed to solve the problem. The operations of job with tardiness or earliness are shifted left or right to optimize the sequence. Simulation results validate the effectiveness of the proposed model and algorithm.

关键词： Assembly job shop tardiness earliness

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Pole placement for discrete-time systems via multiple parametric Lyapunov equations

Pole placement for discrete-time systems via multiple parame...

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International Workshop on Variable Structure systems, VSS

作者： Qingling Wang Yuanda Wang School of Automation Southeast University Nanjing China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

This paper investigates the pole placement problem of discrete-time systems. To retain the advantages of the parametric discrete-time Lyapunov equation, matrix-partitioning idea is used to derive a new pole shift lemma. Starting from system matrix transformations, a recursive method that shifts every eigenvalue of a discrete-time system separately without mode decomposition in each step is proposed. Compared with existing methods, this one not only leads to analytical solutions to feedback gains but also may need low computation cost on flexible pole placement. As an application, the semiglobal stabilization with guaranteed flexible pole placement for saturated discrete-time systems is achieved using this method.

关键词： Linear systems Symmetric matrices Eigenvalues and eigenfunctions Design methodology Discrete-time systems control systems Complex systems

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A robust traffic driver face detection method

A robust traffic driver face detection method

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Dechao Luo Xiaobo Lu Changhui Hu Xiang Peng Wei Wang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781509034857

Face detection technology is a hot topic in the past recent years. It has been maturely applied to many practical areas. However, the driver face detection is still an open problem to solve. In this paper, we proposed an improved method to promote the face detection rate and apply it to the images from the monitoring videos. The first step is to detect the car from the images according to an off-line learning method. Then the method based on additional off-line learning method is the front level for skin color feature in order to correctly detect the driver face. The proposed systems are implemented on the various complicated road environment. The results show that the proposed method improves the efficiency of the driver face detection and is of strong robustness on having glasses, driver head rotation, and lighting change.

关键词： Skin Color Face detection Feature extraction Automobiles Face

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A two-column convolutional neural network for facial point detection

A two-column convolutional neural network for facial point d...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Wei Wang Xiaobo Lu Jiaji Song Cong Chen School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781509034857

This paper proposes a two-column convolutional neural network algorithm for face point detection, which proves better performance than single-column. Because of the deep level structure, global texture features are extracted at higher layers of the network, and the results of keypoint location remains high accuracy. In the first column, we take the R, G, B channel component of original image as input to train the neural network respectively and calculate the average location results. In the second one, we use Sobel operator to extract first-order derivative feature of original image and regard it as the input to train another convolutional network. The location results of two columns above are fused with appropriate proportion to ensure better results. Experimental result on LEW dataset shows the performance of the proposed parallel structure better than single convolutional network, and it stays robust due to occlusions, large pose variations and extreme lighting.

关键词： Neural networks

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Human physical activity recognition based on computer vision with deep learning model

Human physical activity recognition based on computer vision...

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IEEE Instrumentation and measurement Technology Conference

作者： Lingfei Mo Fan Li Yanjia Zhu Anjie Huang School of Instrument Science and Engineering Southeast University Nanjing China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

ISBN: (纸本)9781467392211

Human activity recognition is an active research area in the computer science because it is widely used in the fields of the security monitoring, health assessment, human machine interaction and other human related content searching. In this paper, a computer vision model based on the deep learning algorithm is proposed, which can recognize the human physical activity based on the skeleton data of the human body from the sensor of Microsoft Kinect. This model uses the human skeletons data from the CAD-60 dataset to recognize the human physical activity without using any prior knowledge. It can reduce the works on the stage of data preprocessing and feature extraction. It can also improve the generalization performance and robustness of the model, and give a better understanding of the human physical activity. Different tricks which can improve the performance of the neural networks, such as some regularization methods and other activation functions are tested. Finally, a convolutional neural network is used for the feature extraction, and a multilayer perceptron is used as the following classifier. The model can recognize twelve types of activities and the accuracy rate is 81.8%. It demonstrates that it is very effective to use the convolutional neural network to supervised learning and this model applies to human physical activity recognition.

关键词： Feature extraction Training Skeleton Neurons Computational modeling Biological neural networks Machine learning

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Semi-Global Stabilization for a Class of Nonlinear Time-Delay systems by Linear Output Feedback

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IFAC-PapersOnLine 2015年第12期48卷 185-190页

作者： Wang, Pan Chai, Lin Fei, Shumin Liu, Guquan Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Ministry of Education School of Automation Nanjing 210096 China

The semi-global stabilization problem for a class of nonlinear systems with state time-delay is addressed in this paper. Sufficient conditions are derived by using Lyapunov-Krasovskii functional method and adjusting the scaling gain to guarantee the systems as well as the resulted closed-loop systems under a linear output feedback controller to be semi-globally stable. Numerical example is presented to illustrate the effectiveness of the obtained results in this paper. © 2015, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Closed loop systems

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Boosting-Based One-Class SVM for Recognizing True-Fake Chinese Liquors Using Electronic Noses

Boosting-Based One-Class SVM for Recognizing True-Fake Chine...

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World Congress on Intelligent control and Automation

作者： Zhi-Hua Li Qing-Hao Meng Pei-Feng Qi Yu Zhou Shu-Gen Ma Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems Tianjin University Department of Robotics College of Science and Engineering Ritsumeikan University

ISBN: (纸本)9781467384155

The true-fake detection of Chinese liquors can be considered as a one-class classification problem. Using only positive sample in training process brings about difficulties in determining the optimal parameters of one-class SVM and its kernel. And one-class SVM optimized with conventional grid search method has a low recognition rate of positive test samples. Hence, we proposed a new idea for recognition, namely boosting-based one-class SVM. Six different kinds of liquors were sampled by a self-designed electronic nose system. After the preprocessing and feature extraction of sample data, 18 groups of optimum parameters of one-class SVM were chosen from specified parameter range, each group was used to train a classifier with training algorithm. Then the true-fake decisions were made for test samples with boosting integration rules. Finally the recognition rates of Hongjinjiu and Lanjinjiu positive sample reached 95.24% and 100%, and the recognition rates of both positive and negative sample reached 97.04% and 94.83%, respectively.

关键词： Support Vector Network optimal parameter Electronic Nose Recognition (Psychology) Search methods Chinese Chinese Chinese philosophy Chinese art Feature extraction test sample

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Rapid Detection of Chinese Liquors Using a Portable E-nose Based on C-SVM

Rapid Detection of Chinese Liquors Using a Portable E-nose B...

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World Congress on Intelligent control and Automation

作者： Pei-Feng Qi Qing-Hao Meng Ya-Qi Jing Ming Zeng Shu-Gen Ma Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems Tianjin University Department of Robotics College of Science and Engineering Ritsumeikan University

ISBN: (纸本)9781467384155

We designed a portable electronic nose (e-nose) for rapid detection of Chinese liquors. The e-nose had an evaporation chamber wrapped with silicone heating band, which could vaporize the liquor samples in 1 minute. The sequential sampling and clean-out lasted 100 seconds and 3 minutes, respectively. Hence, one fast detection process could be finished within 3 minutes without regard to clean-out. In order to acquire enough information from array's sampling curves for classification, we chose 60 features (including 6 features per sensor) according to the response curves, the derivative of the response curves and the relative change rate curves of conductivity. Then the dimension of features was reduced by principle component analysis (PCA). Finally, classification of Chinese liquors was performed using C-Support Vector Machine (C-SVM) and the classification rate was 96.7%.

关键词： Sensor arrays Conductivity Principal component analysis Gas detectors Heating Support vector machine classification Support vector machine classification Electronic Nose Gas detectors Sensor arrays principal components analysis conductivity response curves change rate Heating Chinese Chinese Chinese philosophy Chinese art

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