Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822469
S. Memon, W. Lee, T. Song
This paper extends the smoothing algorithm based on integrated probabilistic data association to track multiple maneuvering targets by applying smoothing to joint integrated probabilistic data association (JIPDA). The proposed algorithm utilizes smoothing data association to obtain smoothing prediction which is needed to calculate the smoothing data association probabilities, the smoothing target trajectory state estimates and the smoothing target existence probability. The smoothing data association probabilities are used to update and propagate the forward tracks for tracking multiple maneuvering targets in clutter. This algorithm is called fixed-interval smoothing JIPDA (JIPDAS). Simulation is carried out to show improved false track discrimination performance over the existing algorithms for tracking multiple maneuvering targets in a heavy cluttered environment.
{"title":"Efficient smoothing for multiple maneuvering targets in heavy clutter","authors":"S. Memon, W. Lee, T. Song","doi":"10.1109/ICCAIS.2016.7822469","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822469","url":null,"abstract":"This paper extends the smoothing algorithm based on integrated probabilistic data association to track multiple maneuvering targets by applying smoothing to joint integrated probabilistic data association (JIPDA). The proposed algorithm utilizes smoothing data association to obtain smoothing prediction which is needed to calculate the smoothing data association probabilities, the smoothing target trajectory state estimates and the smoothing target existence probability. The smoothing data association probabilities are used to update and propagate the forward tracks for tracking multiple maneuvering targets in clutter. This algorithm is called fixed-interval smoothing JIPDA (JIPDAS). Simulation is carried out to show improved false track discrimination performance over the existing algorithms for tracking multiple maneuvering targets in a heavy cluttered environment.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131589481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822434
Yanjia Cao, Jing Hu, Tiecheng Song, H. Zhang, Jinghong Guo
An aggregation terminal of the power communication system is proposed in this paper. The terminal takes Samsung Corporation's ARM9 S5PV210 processor as the hardware core, embedded Linux as the operating system. The high-definition network camera is used as the video monitor device, whose interface is Ethernet. The terminal is equipped with 3G/4G LTE and various communication modules and the drivers are transplanted on the ARM Linux system. Based on the link aggregation and the SOCKET communication technology, the software program is designed as the C/S mode using multiple threads of C language. According to experiment results, the terminal can meet the requirements of the video service in the process of electric power communication, improving the efficiency and saving the cost of construction.
{"title":"Design and implementation of power communication terminal based on link aggregation technology","authors":"Yanjia Cao, Jing Hu, Tiecheng Song, H. Zhang, Jinghong Guo","doi":"10.1109/ICCAIS.2016.7822434","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822434","url":null,"abstract":"An aggregation terminal of the power communication system is proposed in this paper. The terminal takes Samsung Corporation's ARM9 S5PV210 processor as the hardware core, embedded Linux as the operating system. The high-definition network camera is used as the video monitor device, whose interface is Ethernet. The terminal is equipped with 3G/4G LTE and various communication modules and the drivers are transplanted on the ARM Linux system. Based on the link aggregation and the SOCKET communication technology, the software program is designed as the C/S mode using multiple threads of C language. According to experiment results, the terminal can meet the requirements of the video service in the process of electric power communication, improving the efficiency and saving the cost of construction.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127288021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822433
D. Kim, B. Vo, B. Vo
Instead of the filtering density, we are interested in the entire posterior density that describes the random set of object trajectories. So far only Markov Chain Monte Carlo (MCMC) technique have been proposed to approximate the posterior distribution of the set of trajectories. Using labeled random finite set we show how the classical multi-object particle filter (a direct generalisation of the standard particle filter to the multi-object case) can be used to recursively compute posterior distribution of the set of trajectories. The result is a generic Bayesian multi-object tracker that does not require re-computing the posterior at every time step nor running a long Markov chain, and is much more efficient than the MCMC approximations.
{"title":"Multi-object particle filter revisited","authors":"D. Kim, B. Vo, B. Vo","doi":"10.1109/ICCAIS.2016.7822433","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822433","url":null,"abstract":"Instead of the filtering density, we are interested in the entire posterior density that describes the random set of object trajectories. So far only Markov Chain Monte Carlo (MCMC) technique have been proposed to approximate the posterior distribution of the set of trajectories. Using labeled random finite set we show how the classical multi-object particle filter (a direct generalisation of the standard particle filter to the multi-object case) can be used to recursively compute posterior distribution of the set of trajectories. The result is a generic Bayesian multi-object tracker that does not require re-computing the posterior at every time step nor running a long Markov chain, and is much more efficient than the MCMC approximations.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128967365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822442
Shoufeng Lin, B. Vo, S. Nordholm
This paper presents a measurement driven birth (MDB) model for the generalized labeled multi-Bernoulli (GLMB) filter. The MDB model adaptively generates target births based on measurement data, thereby eliminating the dependence of a priori knowledge of target birth distributions. Numerical results are provided to demonstrate the performance.
{"title":"Measurement driven birth model for the generalized labeled multi-Bernoulli filter","authors":"Shoufeng Lin, B. Vo, S. Nordholm","doi":"10.1109/ICCAIS.2016.7822442","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822442","url":null,"abstract":"This paper presents a measurement driven birth (MDB) model for the generalized labeled multi-Bernoulli (GLMB) filter. The MDB model adaptively generates target births based on measurement data, thereby eliminating the dependence of a priori knowledge of target birth distributions. Numerical results are provided to demonstrate the performance.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133536045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822435
Dan Li, Hongjian Sun, Wei-Yu Chiu
Smart grid (SG) represents intelligent technologies used to address the climate change. Demand side management (DSM) is an essential part of the SG. This paper establishes a layered model for the DSM. The model involves three participants: power generators, including renewable energy sources, demand response (DR) aggregator, and consumers. The revenue of the DR aggregator is analyzed. The discomfortable level caused by the DSM is considered for consumers. This model leads to a multiobjective (MO) problem. An MO evolutionary algorithm is used to find the Pareto front, facilitating the selection of a fair solution. Simulation results illustrate the feasibility of the proposed approach.
{"title":"A layered approach for enabling demand side management in smart grid","authors":"Dan Li, Hongjian Sun, Wei-Yu Chiu","doi":"10.1109/ICCAIS.2016.7822435","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822435","url":null,"abstract":"Smart grid (SG) represents intelligent technologies used to address the climate change. Demand side management (DSM) is an essential part of the SG. This paper establishes a layered model for the DSM. The model involves three participants: power generators, including renewable energy sources, demand response (DR) aggregator, and consumers. The revenue of the DR aggregator is analyzed. The discomfortable level caused by the DSM is considered for consumers. This model leads to a multiobjective (MO) problem. An MO evolutionary algorithm is used to find the Pareto front, facilitating the selection of a fair solution. Simulation results illustrate the feasibility of the proposed approach.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117300005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822455
Demeng Li, Benlian Xu, Jian Shi
This paper proposes an ant system based state estimation approach for simultaneous localization and mapping (SLAM) in the case of ambiguities both in the feature number and data correspondence. Inspired by the random finite sets (RFS) and its derivative, i.e., probability hypothesis density (PHD), an ant-PHD filtering is proposed to jointly estimate the locations and number of features, moreover, a fast moving ant estimator (F-MAE) is developed for estimating maneuvering vehicle trajectory. In contrast to the state-of-the-art approaches, our algorithm employs the artificial ants instead of simple particles to cluster around their favored regions through ants' positive feedback search mechanism, and also builds a seamless from the filter itself to implementation. Simulated results demonstrate the merits of the proposed approach, which outperforms both the Fast-SLAM and the PHD-SLAM by providing a more accurate map as well as an improved estimate accuracy of the vehicle's trajectory.
{"title":"Ant system based state estimation approach to SLAM","authors":"Demeng Li, Benlian Xu, Jian Shi","doi":"10.1109/ICCAIS.2016.7822455","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822455","url":null,"abstract":"This paper proposes an ant system based state estimation approach for simultaneous localization and mapping (SLAM) in the case of ambiguities both in the feature number and data correspondence. Inspired by the random finite sets (RFS) and its derivative, i.e., probability hypothesis density (PHD), an ant-PHD filtering is proposed to jointly estimate the locations and number of features, moreover, a fast moving ant estimator (F-MAE) is developed for estimating maneuvering vehicle trajectory. In contrast to the state-of-the-art approaches, our algorithm employs the artificial ants instead of simple particles to cluster around their favored regions through ants' positive feedback search mechanism, and also builds a seamless from the filter itself to implementation. Simulated results demonstrate the merits of the proposed approach, which outperforms both the Fast-SLAM and the PHD-SLAM by providing a more accurate map as well as an improved estimate accuracy of the vehicle's trajectory.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131616825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822432
D. Kim
In this paper, we consider a single object visual tracking problem using multi-object filtering technique. We represent object appearance as a multi-object distribution of keypoints. Hidden positions of keypoints are observed by using SURF feature detectors and multi-Bernoulli filtering is used for tracking of keypoints. Unlike other feature matching based object trackers, multi-Bernoulli filtering based tracker is free from combinatorial matching problem. The estimated number of keypoints can be used as a quality measure to determine track re-initialization when it is necessary. Experimental results show that multi-object filtering can be one of effective solutions for single object visual tracking.
{"title":"Multi-Bernoulli filtering for keypoint-based visual tracking","authors":"D. Kim","doi":"10.1109/ICCAIS.2016.7822432","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822432","url":null,"abstract":"In this paper, we consider a single object visual tracking problem using multi-object filtering technique. We represent object appearance as a multi-object distribution of keypoints. Hidden positions of keypoints are observed by using SURF feature detectors and multi-Bernoulli filtering is used for tracking of keypoints. Unlike other feature matching based object trackers, multi-Bernoulli filtering based tracker is free from combinatorial matching problem. The estimated number of keypoints can be used as a quality measure to determine track re-initialization when it is necessary. Experimental results show that multi-object filtering can be one of effective solutions for single object visual tracking.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132556880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822444
Jongmin Yu, Jeonghwan Gwak, M. Jeon
This paper presents a Gaussian-Poisson mixture model (GPMM) which can reflect a frequency of event occurrence, for detecting anomaly of crowd behaviours. GPMM exploits the complementary information of both a statistics of crowd behaviour patterns and a count of the observed behaviour, and we learn the statistics of normal crowd behaviours for behaviours that occur frequently in the past by placing different weights, depending on the frequency occur. GPMM implicitly accounts for the motion patterns and the count of occurrence. The dense optical flow and an interactive force are used to represent a scene. We demonstrate the proposed method on a publicly available dataset, and the experimental results show that the proposed method could achieves competitive performances with respect to state-of-the-art approaches.
{"title":"Gaussian-Poisson mixture model for anomaly detection of crowd behaviour","authors":"Jongmin Yu, Jeonghwan Gwak, M. Jeon","doi":"10.1109/ICCAIS.2016.7822444","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822444","url":null,"abstract":"This paper presents a Gaussian-Poisson mixture model (GPMM) which can reflect a frequency of event occurrence, for detecting anomaly of crowd behaviours. GPMM exploits the complementary information of both a statistics of crowd behaviour patterns and a count of the observed behaviour, and we learn the statistics of normal crowd behaviours for behaviours that occur frequently in the past by placing different weights, depending on the frequency occur. GPMM implicitly accounts for the motion patterns and the count of occurrence. The dense optical flow and an interactive force are used to represent a scene. We demonstrate the proposed method on a publicly available dataset, and the experimental results show that the proposed method could achieves competitive performances with respect to state-of-the-art approaches.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130088125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822436
Long Ge, Jian Shi, Peiyi Zhu
Melt index is considered one of the most important variables in determining chemical product quality and thus reliable prediction of melt index (MI) is essential in practical propylene polymerization processes. In this paper, a fuzzy support vector regression (FSVR) based model for propylene polymerization process is developed to predict the MI of polypropylene from other easily measured process variables. Support vector data description (SVDD) is introduced in this model as a novel fuzzy membership function and to reducing the effect of outliers and noises. A detailed comparison between the standard SVR and SVDD-FSVR models is carried out on a real plant. The research results have confirmed the effectiveness of the presented method.
{"title":"Melt index prediction by support vector regression","authors":"Long Ge, Jian Shi, Peiyi Zhu","doi":"10.1109/ICCAIS.2016.7822436","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822436","url":null,"abstract":"Melt index is considered one of the most important variables in determining chemical product quality and thus reliable prediction of melt index (MI) is essential in practical propylene polymerization processes. In this paper, a fuzzy support vector regression (FSVR) based model for propylene polymerization process is developed to predict the MI of polypropylene from other easily measured process variables. Support vector data description (SVDD) is introduced in this model as a novel fuzzy membership function and to reducing the effect of outliers and noises. A detailed comparison between the standard SVR and SVDD-FSVR models is carried out on a real plant. The research results have confirmed the effectiveness of the presented method.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130192097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICCAIS.2016.7822454
Yingbo Cai, Qian Sun, Ya Zhang, Chunzhu Yu, Hongmei Bai
To improve the positioning accuracy in indoor environments, we use the Inertial Navigation System (INS) algorithm to perform the pedestrian tracking, and the measurements consist of two parts: the velocity error and the heading error. The velocity error can be gotten from the navigation result. Meanwhile, we get the heading error in two ways. First, taking the magnetometer as the heading resource, the magnetic perturbations can be eliminated through a new ellipsoid fitting based calibration algorithm. Furthermore, the building heading algorithm(BHA) is also adopted to aid the Inertial Measurement Unit (IMU), the corresponding building heading can be derived based on the motion path. Finally, the Kalman filter (KF) is utilized to fuse the data in order to compensate the sensor error and navigation solution through a 15-dimentional state vector. As a result, some field trials were taken to prove the validity of the proposed algorithm. By contrast the result of Magnetometer (MAG)/BHA/INS and the Zero Velocity update (ZUPT) algorithms, we proved that the algorithm of MAG/BHA aiding INS can effectively improve the indoor positioning accuracy which shows better performance.
{"title":"Integrated navigation for pedestrian with building heading algorithm and inertial measurement unit","authors":"Yingbo Cai, Qian Sun, Ya Zhang, Chunzhu Yu, Hongmei Bai","doi":"10.1109/ICCAIS.2016.7822454","DOIUrl":"https://doi.org/10.1109/ICCAIS.2016.7822454","url":null,"abstract":"To improve the positioning accuracy in indoor environments, we use the Inertial Navigation System (INS) algorithm to perform the pedestrian tracking, and the measurements consist of two parts: the velocity error and the heading error. The velocity error can be gotten from the navigation result. Meanwhile, we get the heading error in two ways. First, taking the magnetometer as the heading resource, the magnetic perturbations can be eliminated through a new ellipsoid fitting based calibration algorithm. Furthermore, the building heading algorithm(BHA) is also adopted to aid the Inertial Measurement Unit (IMU), the corresponding building heading can be derived based on the motion path. Finally, the Kalman filter (KF) is utilized to fuse the data in order to compensate the sensor error and navigation solution through a 15-dimentional state vector. As a result, some field trials were taken to prove the validity of the proposed algorithm. By contrast the result of Magnetometer (MAG)/BHA/INS and the Zero Velocity update (ZUPT) algorithms, we proved that the algorithm of MAG/BHA aiding INS can effectively improve the indoor positioning accuracy which shows better performance.","PeriodicalId":407031,"journal":{"name":"2016 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129092547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：