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  • Open Access


    Intelligent Traffic Surveillance through Multi-Label Semantic Segmentation and Filter-Based Tracking

    Asifa Mehmood Qureshi1, Nouf Abdullah Almujally2, Saud S. Alotaibi3, Mohammed Hamad Alatiyyah4, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3707-3725, 2023, DOI:10.32604/cmc.2023.040738

    Abstract Road congestion, air pollution, and accident rates have all increased as a result of rising traffic density and worldwide population growth. Over the past ten years, the total number of automobiles has increased significantly over the world. In this paper, a novel method for intelligent traffic surveillance is presented. The proposed model is based on multilabel semantic segmentation using a random forest classifier which classifies the images into five classes. To improve the results, mean-shift clustering was applied to the segmented images. Afterward, the pixels given the label for the vehicle were extracted and blob detection was applied to mark… More >

  • Open Access


    Strong Tracking Particle Filter Based on the Chi-Square Test for Indoor Positioning

    Lingwu Qian1, Jianxiang Li2, Qi Tang1, Mengfei Liu1, Bingjie Yuan1, Guoli Ji1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1441-1455, 2023, DOI:10.32604/cmes.2023.024534

    Abstract In recent years, a number of wireless indoor positioning (WIP), such as Bluetooth, Wi-Fi, and Ultra-Wideband (UWB) technologies, are emerging. However, the indoor environment is complex and changeable. Walls, pillars, and even pedestrians may block wireless signals and produce non-line-of-sight (NLOS) deviations, resulting in decreased positioning accuracy and the inability to provide people with real-time continuous indoor positioning. This work proposed a strong tracking particle filter based on the chi-square test (SPFC) for indoor positioning. SPFC can fuse indoor wireless signals and the information of the inertial sensing unit (IMU) in the smartphone and detect the NLOS deviation through the… More >

  • Open Access


    Integrating WSN and Laser SLAM for Mobile Robot Indoor Localization

    Gengyu Ge1,2,*, Zhong Qin1, Xin Chen1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6351-6369, 2023, DOI:10.32604/cmc.2023.035832

    Abstract Localization plays a vital role in the mobile robot navigation system and is a fundamental capability for the following path planning task. In an indoor environment where the global positioning system signal fails or becomes weak, the wireless sensor network (WSN) or simultaneous localization and mapping (SLAM) scheme gradually becomes a research hot spot. WSN method uses received signal strength indicator (RSSI) values to determine the position of the target signal node, however, the orientation of the target node is not clear. Besides, the distance error is large when the indoor signal receives interference. The laser SLAM-based method usually uses… More >

  • Open Access


    Aluminum Alloy Fatigue Crack Damage Prediction Based on Lamb Wave-Systematic Resampling Particle Filter Method

    Gaozheng Zhao1, Changchao Liu1, Lingyu Sun1, Ning Yang2, Lei Zhang1, Mingshun Jiang1, Lei Jia1, Qingmei Sui1,*

    Structural Durability & Health Monitoring, Vol.16, No.1, pp. 81-96, 2022, DOI:10.32604/sdhm.2022.016905

    Abstract Fatigue crack prediction is a critical aspect of prognostics and health management research. The particle filter algorithm based on Lamb wave is a potential tool to solve the nonlinear and non-Gaussian problems on fatigue growth, and it is widely used to predict the state of fatigue crack. This paper proposes a method of lamb wave-based early fatigue microcrack prediction with the aid of particle filters. With this method, which the changes in signal characteristics under different fatigue crack lengths are analyzed, and the state- and observation-equations of crack extension are established. Furthermore, an experiment is conducted to verify the feasibility… More >

  • Open Access


    Recognition and Tracking of Objects in a Clustered Remote Scene Environment

    Haris Masood1, Amad Zafar2, Muhammad Umair Ali3, Muhammad Attique Khan4, Salman Ahmed1, Usman Tariq5, Byeong-Gwon Kang6, Yunyoung Nam6,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1699-1719, 2022, DOI:10.32604/cmc.2022.019572

    Abstract Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer Vision. Computer vision is one of the most active research fields that lies at the intersection of deep learning and machine vision. This paper presents an efficient ensemble algorithm for the recognition and tracking of fixed shape moving objects while accommodating the shift and scale invariances that the object may encounter. The first part uses the Maximum Average Correlation Height (MACH) filter for object recognition and determines the bounding box coordinates. In case the correlation based MACH filter fails, the algorithms… More >

  • Open Access


    Estimation Performance for the Cubature Particle Filter under Nonlinear/Non-Gaussian Environments

    Dah-Jing Jwo1,*, Chien-Hao Tseng2

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1555-1575, 2021, DOI:10.32604/cmc.2021.014875

    Abstract This paper evaluates the state estimation performance for processing nonlinear/non-Gaussian systems using the cubature particle filter (CPF), which is an estimation algorithm that combines the cubature Kalman filter (CKF) and the particle filter (PF). The CPF is essentially a realization of PF where the third-degree cubature rule based on numerical integration method is adopted to approximate the proposal distribution. It is beneficial where the CKF is used to generate the importance density function in the PF framework for effectively resolving the nonlinear/non-Gaussian problems. Based on the spherical-radial transformation to generate an even number of equally weighted cubature points, the CKF… More >

  • Open Access


    Research on Time Synchronization Method Under Arbitrary Network Delay in Wireless Sensor Networks

    Bing Hu1, Feng Xiang2, Fan Wu3, Jian Liu4, Zhe Sun1, Zhixin Sun1,*

    CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1323-1344, 2019, DOI:10.32604/cmc.2019.06414

    Abstract To cope with the arbitrariness of the network delays, a novel method, referred to as the composite particle filter approach based on variational Bayesian (VB-CPF), is proposed herein to estimate the clock skew and clock offset in wireless sensor networks. VB-CPF is an improvement of the Gaussian mixture kalman particle filter (GMKPF) algorithm. In GMKPF, Expectation-Maximization (EM) algorithm needs to determine the number of mixture components in advance, and it is easy to generate overfitting and underfitting. Variational Bayesian EM (VB-EM) algorithm is introduced in this paper to determine the number of mixture components adaptively according to the observations. Moreover,… More >

  • Open Access


    A New Optimized Algorithm with Nonlinear Filter for Ultra-Tightly Coupled Integrated Navigation System of Land Vehicle

    Chien-Hao Tseng1, Dah-Jing Jwo2, Chih-Wen Chang1

    CMC-Computers, Materials & Continua, Vol.27, No.1, pp. 23-54, 2012, DOI:10.3970/cmc.2012.027.023

    Abstract The extended particle filter (EPF) assisted by the Takagi-Sugeno (T-S) fuzzy logic adaptive system (FLAS) is used to design the ultra-tightly coupled GPS/INS (inertial navigation system) integrated navigation, which can maneuver the vehicle environment and the GPS outages scenario. The traditional integrated navigation designs adopt a loosely or tightly coupled architecture, for which the GPS receiver may lose the lock due to the interference/jamming scenarios, high dynamic environments, and the periods of partial GPS shading. An ultra-tight GPS/INS architecture involves the integration of I (in-phase) and Q (quadrature) components from the correlator of a GPS receiver with the INS data.… More >

  • Open Access


    Improved Adaptive Particle Filter for Integrated Navigation System

    Mengchu Tian1, Yuming Bo1, Zhimin Chen2,3, Panlong Wu1, Gaopeng Zhao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.108, No.5, pp. 285-301, 2015, DOI:10.3970/cmes.2015.108.285

    Abstract Particle filter based on particle swarm optimization algorithm is not precise enough and easily trapping in local optimum, it is difficult to satisfy the requirement of advanced integrated navigation system. To solve these problems, an improved adaptive particle filter based on chaos particle swarm was proposed and used in GPS/INS integrated navigation system. This algorithm introduced chaos sequence to update the weight and threshold, which could improve the quality of samples and reduce the local optimization and enhance the global searching ability. In addition, the avoid factor was set which made the particles be away from low likelihood area. Finally,… More >

  • Open Access


    Hybrid Adaptive Particle Swarm Optimized Particle Filter for Integrated Navigation System

    Zhimin Chen1,2, Yuanxin Qu1, Tongshuang Zhang1, Xiaoshu Bai1, Xiaohong Tao1, Yong Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.106, No.6, pp. 379-393, 2015, DOI:10.3970/cmes.2015.106.379

    Abstract Particle swarm optimization algorithm based particle filter is trapping in local optimum easily, it is not able to satisfy the requirement of modern integrated navigation system. In order to solve the problem, A novel particle filter algorithm based on hybrid adaptive particle swarm optimization(HPSO-PF) is presented in this paper. This improved particle filter will conduce to finding the ideal solution domain by making use of the global convergence of artificial fish swarm and enhancement of fusion precision by guiding particles to move toward the high likelihood area through particle swarm optimization. Finally different models are used for simulation and the… More >

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