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31st Youth Academic Annual Conference of Chinese-Association-of-Automation (YAC)

作者： Lu, Zhou Cai, Yunze He, Jie Wang, Sheyang Shanghai Jiao Tong Univ Shanghai Peoples R China CASC Res Inst 8 Shanghai Peoples R China

ISBN: (纸本)9781509044238

Because of the unique flight trajectory and high penetration effectiveness, near-space hypersonic vehicles (NSHV) become a great challenge for active air defense systems. This paper study the tracking algorithm for NSHV based on Aerodynamic Model. Firstly, the paper simulated flight trajectory of NSHV based on the equation of motion. Secondly, the paper designed a tracking method for NSHV by using aerodynamic acceleration model. the effectiveness and limitation of the model are both verified by simulation. Finally, this paper provided some suggestions for improvement of the tracking algorithm based on Aerodynamic Acceleration Model.

关键词： flight orbit simulation of NSHV aerodynamic acceleration model tracking algorithm

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Automated time-resolved tracking algorithm of the atrioventricular plane displacement in CMR images

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Journal of Cardiovascular Magnetic Resonance 2016年第SUPPL 1期18卷 P43-P43页

作者： Felicia Seemann Ulrika Pahlm Katarina Steding-Ehrenborg Ellen Ostenfeld Håkan Arheden Marcus Carlsson Einar Heiberg Department of Clinical Physiology Skåne University Hospital Lund University Lund Sweden Department of Health Sciences Lund University Lund Sweden Department of Biomedical Engineering Faculty of Engineering Lund University Lund Sweden

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The Mean Shift tracking algorithm With Adaptive Bandwidth Based on Affine Transformation 12

The Mean Shift Tracking Algorithm With Adaptive Bandwidth Ba...

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12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Lv, Lixia Yan, Chenghan North China Elect Power Univ Dept Automat Baoding Peoples R China

ISBN: (纸本)9781467376822

The kernel bandwidth of the traditional Mean Shift tracking algorithm cannot be changed in real time. It can't achieve accurate tracking when the target size is changing. This paper proposes an algorithm to automatically select the bandwidth of the kernel function, which can achieve accurate tracking when the size of the rigid target is changing. Firstly, it matches the target center of two consecutive frames by using the backward tracking. Then in order to effectively eliminate the false matching and ensure the accuracy of the regression, it extracts and disposes the feature points with regressive calculation on the base of matching. The results of tracking experiment show that the proposed algorithm can achieve accurate tracking in real time when the target size is changing.

关键词： kernel kernel bandwidth Mean Shift tracking algorithm backward tracking regressive calculation

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A Distributed algorithm for tracking General Functions of Multiple Signals Not-Necessarily Having Steady States

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2021年第6期68卷 2107-2111页

作者： Wang, Wuguang Chen, Fei Xiang, Linying Chen, Guanrong Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110004 Peoples R China Northeastern Univ Qinhuangdao Sch Control Engn Qinhuangdao 066004 Hebei Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

This brief exploits the possibility of devising an algorithm for tracking a general function pertaining to multiple signals from a multi-agent system in a distributed sense, where each agent has access to one single signal. Each agent's input relies solely on local neighboring information, from which some conditions on the gain parameters, the reference signals, along with the general function, are derived such that the tracking objective is attainable. The algorithm is well-defined as long as the gradient of the general function with respect to agents' states has a uniform lower bound. Under mild conditions, it is shown that the devised system is able to track a general consensus function of multiple dynamic signals, including arithmetic mean, geometric mean, and root-mean square as special examples. The effectiveness of the proposed algorithm is demonstrated via numerical examples.

关键词： Multi-agent systems Heuristic algorithms Task analysis Circuits and systems Optimization Graph theory Eigenvalues and eigenfunctions tracking algorithm signum function non-smooth analysis

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Parking Time Violation tracking Using YOLOv8 and tracking algorithms

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SENSORS 2023年第13期23卷 5843-5843页

作者： Sharma, Nabin Baral, Sushish Paing, May Phu Chawuthai, Rathachai King Mongkuts Inst Technol Ladkrabang Sch Engn Dept Robot & AI Bangkok 10520 Thailand King Mongkuts Inst Technol Ladkrabang Sch Engn Dept Biomed Engn Bangkok 10520 Thailand King Mongkuts Inst Technol Ladkrabang Sch Engn Dept Comp Engn Bangkok 10520 Thailand

The major problem in Thailand related to parking is time violation. Vehicles are not allowed to park for more than a specified amount of time. Implementation of closed-circuit television (CCTV) surveillance cameras along with human labor is the present remedy. However, this paper presents an approach that can introduce a low-cost time violation tracking system using CCTV, Deep Learning models, and object tracking algorithms. This approach is fairly new because of its appliance of the SOTA detection technique, object tracking approach, and time boundary implementations. YOLOv8, along with the DeepSORT/OC-SORT algorithm, is utilized for the detection and tracking that allows us to set a timer and track the time violation. Using the same apparatus along with Deep Learning models and algorithms has produced a better system with better performance. The performance of both tracking algorithms was well depicted in the results, obtaining MOTA scores of (1.0, 1.0, 0.96, 0.90) and (1, 0.76, 0.90, 0.83) in four different surveillance data for DeepSORT and OC-SORT, respectively.

关键词： DeepSORT OC-SORT object detection tracking algorithm vehicle tracking YOLOv8

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A Distributed algorithm for tracking General Functions in Disturbed Multi-agent Systems

A Distributed Algorithm for Tracking General Functions in Di...

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第43届中国控制会议

作者： Ruixin Jiang Haotian Wang Fei Chen College of Information Science and Engineering Northeastern University College of Artificial Intelligence Nankai University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper tackles the challenge of tracking general functions of multiple signals within disturbed first-order multi-agent systems. In this context, a team of agents collaboratively monitors time-varying signals, even when disturbances disrupt the dynamics of the single-integrator agent. Each agent relies on locally available information from its neighboring agents. The paper establishes conditions for the gain parameters, reference signals, and functions, ensuring the attainability of the tracking objective. The proposed system demonstrates its ability to track various functions of time-varying signals, including arithmetic mean, geometric mean, and root-mean square. Simulation results provide empirical validation of the algorithm's effectiveness.

关键词： Disturbed multi-agent systems tracking algorithm Non-smooth system

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tracking algorithms for TPCs using consensus-based robust estimators

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2021年 988卷 164899-164899页

作者： Zamora, J. C. Fortino, G. F. Univ Sao Paulo Inst Fis BR-05508090 Sao Paulo Brazil

A tracking algorithm(1) based on consensus-robust estimators was implemented for the analysis of experiments with time-projection chambers. In this work, few algorithms beyond RANSAC were successfully tested using experimental data taken with the AT-TPC, ACTAR and TexAT detectors. The present tracking algorithm has a better inlier-outlier detection than the simple sequential RANSAC routine. Modifications in the random sampling and clustering were included to improve the tracking efficiency. Very good results were obtained in all the test cases, in particular for fitting short tracks in the detection limit.

关键词： Time Projection Chambers Active Target tracking algorithm RANSAC Clustering

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A Perceptually Adaptive Long-Term tracking Method for the Complete Occlusion and Disappearance of a Target

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COGNITIVE COMPUTATION 2023年第6期15卷 2120-2131页

作者： Chen, Lu Li, Gun Zhao, Kunqi Zhang, Guiping Zhu, Xingyu Univ Elect Sci & Technol China Sch Aeronaut & Astronaut Chengdu 611731 Peoples R China Zhongxing Telecommun Equipment Corp Shenzhen 518057 Peoples R China

In recent years, tracking algorithms based on correlation filtering have been widely considered because of their high real-time performance. However, most of these algorithms do not consider the reliability of tracking results;thus, model drift is often a challenge in long-term target tracking. Moreover, the target is significantly occluded or disappears in long-term target tracking, hence the need for research to address such complexities. This paper proposes a long-term tracking framework comprising a tracking and re-detection module. The tracking module is based on the efficient convolution operator target-tracking algorithm (ECO) (Danelljan et al. in Proc IEEE Conf Comput Vis Pattern Recognit, 1). To redetect a lost target, a tracking uncertainty estimation method is developed that evaluates the tracking results of each image. Furthermore, an adaptive model-updating method is proposed, which can reduce the number of model updates and improve the robustness of the tracking algorithm. The model is inspired by long and short-term memory pool mechanisms of the brain, applying both mechanisms to the traditional tracking algorithm to improve long-term tracking. The memory model is effectively integrated into a brain-inspired visual long-term tracker through mutual learning and inspiration from computer and biological vision. In addition, the brain-inspired visual model can be made bio-cognitive on a small hardware platform with limited computing power. Central processing unit (CPU)-based experiments using two data sets, UAV20L (Mueller et al. in Eur Conf Comput Vision, 2) and UAV123 (Wu et al. in Proc IEEE Conf Comput Vis Pattern Recognit, 3), confirmed that the proposed method runs faster than 30fps. Furthermore, the long-term tracking test using the UAV20L data set showed that the proposed method performs better than any other method by 39%. Compared with conventional tracking methods, the proposed method has better performance in terms of coverage rate and position

关键词： Long-term target tracking tracking algorithm Uncertainty estimation method Adaptive model-updating method

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Efficiency Improvement for Path Detection and tracking algorithm in a Time-Varying Channel

Efficiency Improvement for Path Detection and Tracking Algor...

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IEEE Vehicular Technology Conference

作者： Rui Wang Olivier Renaudin Ricardo M. Bernas Andreas F. Molisch Ming Hsieh Dept. of Electr. Eng. Univ. of Southern California Los Angeles CA USA

ISBN: (纸本)9781479980925

This paper revisits estimation and tracking of channel parameters of multiple-input multiple-output (MIMO) systems. Since the initialization of channel parameters has always been regarded as a computationally complex problem, we develop a new parameter initialization method that exploits the nature of the data structure of channel measurements. For medium or large problems it leads to a more than 500 times runtime acceleration for parameter initialization. We show that the runtime of the new initialization method increases more slowly compared with that of the traditional initialization method when the dimensions of measurement data or search grids grow.

关键词： Efficiency Improvement Path Detection tracking algorithm initialization time-varying channels Runtime multiple input multiple output systems channel measurement tracking measurement data

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A robust occupancy detection and tracking algorithm for the automatic monitoring and commissioning of a building

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ENERGY AND BUILDINGS 2014年 77卷 270-280页

作者： Shih, Huang-Chia Yuan Ze Univ Dept Elect Engn Human Comp Interact Multimedia Lab Taoyuan Taiwan

The focus of this study is the 24 h a day monitoring of buildings for commissioning purposes. Based on an image-based depth sensor and a programmable pan-tilt-zoom (PTZ) camera, the proposed monitoring system enables the continuous detection and tracking of the occupants, even under dim-lighting conditions. The proposed SVM-based observation measurement provides a more reliable tracking performance. This paper presents a robust day-and-night people tracking and counting algorithm. The function of large-scale field monitoring is realized using a PTZ camera network instead of a conventional fixed camera. Furthermore, based on the depth image sensor, the contour information of the occupant can be applied for more accurate activity recognition. In our experiments we demonstrated the positive result of the occupancy detection and tracking algorithms applied to count people and monitor a building. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Building control Commissioning Building management system (BMS) Building monitoring Intelligent-controlled environment Occupancy detection tracking algorithm

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