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IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference

作者： Wang, Ning Wang, Chengfu Niu, Yuanfang Yang, Ming Yu, Yixiao Shandong Univ Jingshi Rd Jinan Peoples R China Jingshi Rd Jinan Peoples R China Shandong Elect Power Engn Consulting Inst Co Ltd Jinan Peoples R China

ISBN: (纸本)9781728171951

The large-scale sharing electric vehicle (SEV) need adequate charging infrastructure to maintain the optimal operation. Considering the convenience of SEV users' charging during driving, a two-stage planning method combining charging stations and scattered charging piles for SEV is proposed to balance the economy of charging system and the convenience of SEVs user. In the first stage, according to the urban area division and trip characteristics of SEV, charging power demand of SEV in planning area can be estimated exactly. Then, aiming for the minimum annual total cost, and the mean clustering algorithm and queuing theory are used to determine the location and capacity of charging stations. In the second stage, an improved S-shaped function is used to assessment the unsatisfactory charging demand, and the compensated charging pile without in the station is planned based on the mean shift algorithm. Based on the re-division of the service scope, the capacity of the charging stations is updated. Finally, the simulation results verify the proposed model and algorithm is effective and feasible.

关键词： charging facility mean clustering mean shift algorithm queuing theory sharing electric vehicle two-stage planning

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Generalized Transport mean shift algorithm for ubiquitous intelligence

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SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL 2012年第10期88卷 1202-1215页

作者： Sunat, Khamron Padungweang, Panida Chiewchanwattana, Sirapat Khon Kaen Univ Dept Comp Sci Fac Sci Khon Kaen 40002 Thailand

Much research has been conducted recently relating to ubiquitous intelligent computing. Ubiquitous intelligence-enabled techniques, such as clustering and image segmentation, have focused on the development of intelligence methodologies. In this paper, a simultaneous mode-seeking and clustering algorithm called the Generalized Transport mean shift (GTMS) was introduced. The data points were designated as the 'transporter-trailer' characteristic. The important concept of transportation was used to solve the problem of redundant computations of mode-seeking algorithms. The time complexity of the GTMS algorithm is much lower than that of the mean shift (MS) algorithm. This means it is able to be used in a problem that has a very high data point, in particular, the segmentation of images containing the green vegetation. The proposed algorithm was tested on clustering and image-segmentation problems. The experimental results showed that the GTMS algorithm improves upon the existing algorithms in terms of both accuracy and time consumption. The GTMS algorithm's highest speed is also 333.98 times faster than that of the standard MS algorithm. The redundancy computation can be reduced by omitting more than 90% of the data points at the third iteration of the mode-seeking process. This is because GTMS algorithm mainly reduces the data in the mode-seeking process. Thus, use of the GTMS algorithm would allow for the building of an intelligent portable device for surveying green vegetables in a ubiquitous environment.

关键词： mean shift algorithm agglomerative mean shift clustering Generalized Transport mean shift algorithm image segmentation clustering mode seeking ubiquitous intelligence

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A Novel Vehicle Tracking algorithm Based on mean shift and Active Contour Model in Complex Environment 2

A Novel Vehicle Tracking Algorithm Based on Mean Shift and A...

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Conference on Automated Visual Inspection and Machine Vision II

作者： Cai, Lei Wang, Lin Li, Bo Zhang, Libao Lv, Wen Minist Commun ITSC Res Inst Highway Key Lab Intelligent Transportat Syst Technol Beijing 100088 Peoples R China Beijing Normal Univ Coll Informat Sci & Technol 19 Xinjiekouwai Rd Beijing 100875 Peoples R China

ISBN: (纸本)9781510611146;9781510611139

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, mean-shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. meanwhile, the outline information is used to aid tracking algorithm to improve it.

关键词： Machine vision image processing target recognition object tracking mean shift algorithm active contour model

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Gesture Tracking and Locating algorithm Based on Federated Tracking Filter

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JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME 2019年第12期141卷 1-6页

作者： Yu, Lei Hou, Junyi Fei, Shumin Soochow Univ Sch Mech & Elect Engn Suzhou 215006 Peoples R China Chongqing Univ Posts & Telecommun Key Lab Ind Internet Things & Networked Control Minist Educ Chongqing 400065 Peoples R China Zhejiang Univ State Key Lab CAD & CG Hangzhou 310027 Peoples R China Southeast Univ Sch Automat Nanjing 210096 Peoples R China

In this paper, a joint gesture tracking method combining particle filter and mean shift algorithm is proposed to improve the accuracy and robustness of the system. During the slow movement of the human hand, the average movement of the particles is first used to cause most of the particles to drift into the gesture area. In the case where the movement of the human hand is faster or there is occlusion, when the mean shift of the particle is performed, if the region of the gesture is not detected, the particle will return to the state before the drift, and then the next frame is processed. The method can directly calculate the position of the gesture based on the particles used for subsequent testing, and can save the tracking time of the algorithm. Through experimental simulation, compared with the Cam-shift algorithm, when the sampling point of the joint tracking algorithm proposed in this paper is 200, the tracking accuracy is improved to 95.2%. Compared with 90.6% of the Cam-shift algorithm, the tracking time is reduced from 83.7ms to 25.8ms. Therefore, the proposed algorithm can greatly improve the tracking accuracy and real-time, and can also effectively reduce the impact of complex environments on the tracking effect.

关键词： human-computer interaction federated tracking algorithm dynamic gesture tracking particle filter mean shift algorithm

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Bandwidth selection for nonparametric modal regression

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2019年第4期48卷 968-984页

作者： Zhou, Haiming Huang, Xianzheng Northern Illinois Univ Div Stat De Kalb IL USA Univ South Carolina Dept Stat Columbia SC 29208 USA

In the context of estimating local modes of a conditional density based on kernel density estimators, we show that existing bandwidth selection methods developed for kernel density estimation are unsuitable for mode estimation. We propose two methods to select bandwidths tailored for mode estimation in the regression setting . Numerical studies using synthetic data and a real-life dataset are carried out to demonstrate the performance of the proposed methods in comparison with several well-received bandwidth selection methods for density estimation.

关键词： Bootstrap Cross-validation Hausdorff distance mean shift algorithm

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Mixture model modal clustering

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ADVANCES IN DATA ANALYSIS AND CLASSIFICATION 2019年第2期13卷 379-404页

作者： Chacon, Jose E. Univ Extremadura Dept Matemat Badajoz 06006 Spain

The two most extended density-based approaches to clustering are surely mixture model clustering and modal clustering. In the mixture model approach, the density is represented as a mixture and clusters are associated to the different mixture components. In modal clustering, clusters are understood as regions of high density separated from each other by zones of lower density, so that they are closely related to certain regions around the density modes. If the true density is indeed in the assumed class of mixture densities, then mixture model clustering allows to scrutinize more subtle situations than modal clustering. However, when mixture modeling is used in a nonparametric way, taking advantage of the denseness of the sieve of mixture densities to approximate any density, then the correspondence between clusters and mixture components may become questionable. In this paper we introduce two methods to adopt a modal clustering point of view after a mixture model fit. Examples are provided to illustrate that mixture modeling can also be used for clustering in a nonparametric sense, as long as clusters are understood as the domains of attraction of the density modes. Finally, a simulation study reveals that the new methods are extremely efficient from a computational point of view, while at the same time they retain a high level of accuracy.

关键词： Mixture modeling Modal clustering Component merging mean shift algorithm

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Video based crowd stability analysis used in emegency evacuation 3

Video based crowd stability analysis used in emegency evacua...

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IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

作者： Zhao, Rongyong Dong, Daheng Li, Cuiling Liu, Qiong Hu, Qianshan Ma, Yunlong Zhang, Qin Tongji Univ CIMS Res Ctr Shanghai 201804 Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China Shanghai Maritime Univ Elect Engn & Automat Dept Shanghai 201306 Peoples R China

ISBN: (纸本)9781538662434

The study of crowd stability in emergency evacuation is great significant to the public safety. In this paper, we put forward a video based crowd stability analysis model. In this model, we conduct a study on crowd flow video in public places to analyze the stability of crowd and provide valuable guidance for public safety management. Firstly, we use Hough circle transform and mean shift algorithm to respectively detect crowd density and pedestrian movement trajectory, and further calculate crowd velocity. Then, according to the stability criterion of crowd evacuation proposed by The Green Guide, we analyze the stability of crowd in the video. According to the results of stability analysis, the safety management department could take timely safety measures. Finally, the effectiveness of the method proposed in this paper is validated through case study.

关键词： video crowd evacuation stability Hough circle transform mean shift algorithm stability criterion

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Real Time Fish Tracking Method Based on xPC Target 3

Real Time Fish Tracking Method Based on xPC Target

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IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

作者： Liu Yaqi Zhang Lei Shi Xiaobin Henan Univ Sch Phys & Elect Kaifeng Peoples R China

ISBN: (纸本)9781538662434

The research on the mechanism of flexible bionic fish propulsion based on modal analysis is to develop a highspeed and efficient bionic swing propeller by studying the relationship between the swing frequency of soft-body bionic fish and its velocity. How to accurately track the real-time path of bionic fish has become the core issue of developing propellers. The motion estimation by an improvement mean shift algorithm is added to track the path of the bionic fish on xPC-Target platform. According to dual-target setting, two-dimensional coordinates are converted to three-dimensional coordinates. The position coordinates of the bionic fish swimming in real time are obtained. The actual position of fish swimming is compared with the tracking position, which determines the tracking accuracy.

关键词： Bionic fish propeller mean shift algorithm trajectory tracking

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On-line Data Analysis and Optimization of Crankshaft Dynamic Balance 3

On-line Data Analysis and Optimization of Crankshaft Dynamic...

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3rd International Conference on Artificial Intelligence Applications and Technologies (AIAAT)

作者： Zhou, Chuanhong Ding, Lei Lin, Lianghuang Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Intelligent Mfg & Robot Shanghai Peoples R China

The crankshaft is a high-speed rotating component that is widely used in many fields. Dynamic balance of the crankshaft is an important process stage that affects the quality of the crankshaft. In order to optimize the quality of crankshaft dynamic balance machining, this paper illustrates the importance of the initial unbalance of crankshaft to the dynamic balance machining of crankshaft. For the initial imbalance distribution of crankshaft, the improved mean method, gradient descent method and mean shift algorithm are used to calculate the machining center. The position of the hole realizes the crankshaft imbalance correction with different effects and reduces the processing strength of the crankshaft dynamic balance phase. The study is applicable to the machining of crankshafts in geometric centering processes in batches.

关键词： crankshaft dynamic balance online control mean method gradient descent method mean shift algorithm

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Anti-occlusion tracking algorithm of video target based on prediction and re-matching strategy

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2018年 57卷 176-182页

作者： Hu, Zhen-tao Zhou, Lin Yang, Ya-nan Liu, Xian-xing Jin, Yong Henan Univ Coll Comp & Informat Engn Kaifeng 475004 Peoples R China

Accurately locating the video target in the process of occlusion and recurrence will be very important for effective follow-up of the target For the problem of poor applicability of mean shift and its improved algorithm when the target is heavily occluded, this paper proposes an anti-occlusion video target tracking algorithm based on prediction and re-matching strategy. Firstly, dynamically combining the mean shift algorithm with the Kalman filter, this paper achieves stable tracking of un-occluded target. Secondly, when the target is occluded, Kalman filter is combined with the target prior information to predict the position of the occluded target. Finally, in the recurrence process of occluded targets, the target is re- matched through the normalized cross-correlation method to obtain target optimal position, and then the target can be quickly and accurately located. The simulation results show that the proposed method has strong anti-occlusion and reliability tracking in the video target tracking process. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Anti-occlusion mean shift algorithm Kalman filter Normalized cross correlation matching

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