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2009 IEEE 12th International Conference on computer Vision Workshops, ICCV Workshops 2009

作者： Zhang, Xiaoqin Hu, Weiming Li, Wei Qu, Wei Maybank, Steve National Laboratory of Pattern Recognition Institute of Automation Beijing China Siemens Medical Solutions USA Inc. IL United States School of Computer Science and Information Systems Birkbeck College London United Kingdom

ISBN: (纸本)9781424444427

Multiple object tracking is particularly challenging when many objects with similar appearances occlude one another. Most existing approaches concatenate the states of different objects, view the multi-object tracking as a joint motion estimation problem and search for the best state of the joint motion in a rather high dimensional space. However, this centralized framework suffers a great computational load. We brings a new view to the tracking problem from a swarm intelligence perspective. In analogy with the foraging behavior of the bird flocks, we propose a species based PSO (particle swarm optimization) algorithm for multiple object tracking, in which the global swarm is divided into many species according to the number of objects, and each species searches for its object and maintains it. The interaction between different objects is modeled as species competition and repulsion, and the occlusion relationship is implicitly deduced from the 'power' of each species, which is effectively evaluated by the image observations. Therefore, our approach decentralizes the joint tracker to a set of individual trackers, each of which tries to maximize its visual evidence. Experimental results demonstrate the efficiency and effectiveness of our method. ©2009 IEEE.

关键词： Particle swarm optimization (PSO)

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Freshness-aware Incentive Mechanism for Mobile AI-Generated Content (AIGC) Networks

Freshness-aware Incentive Mechanism for Mobile AI-Generated ...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Wen, Jinbo Kang, Jiawen Xu, Minrui Du, Hongyang Xiong, Zehui Zhang, Yang Niyato, Dusit Guangdong University of Technology School of Automation China Nanyang Technological University School of Computer Science and Engineering Singapore Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology China

ISBN: (纸本)9798350345384

Artificial Intelligence-Generated Content (AIGC) is a rapidly growing field that uses advanced AI algorithms to automatically generate, manipulate, and modify data to create diverse and valuable content. Recently, mobile AIGC networks have attracted significant attention. They integrate with mobile edge networks to provide customized and personalized AIGC services in real time. This is achieved by deploying AI algorithms on edge devices, particularly on Unmanned Aerial Vehicles (UAVs) with edge servers in a flexible and dynamic manner for ubiquitous edge intelligence. However, the wide deployment of UAV-enabled AIGC still faces critical challenges, such as issues with data freshness for AIGC fine-tuning and concerns around incentivizing fresh data sharing among UAVs under information asymmetry. In this paper, we first utilize Age of information (AoI) as a well-accepted data-freshness metric to quantify data freshness for AIGC fine-tuning. Then, we propose an AoI-based contract theory model to incentivize the contribution of fresh data among UAVs. Moreover, we design the optimal contract that is feasible to maximize the expected utility of the base station that is responsible for dispatching UAVs to collaboratively perform AIGC tasks. Finally, numerical results demonstrate the effectiveness of the proposed scheme in mobile AIGC networks. © 2023 IEEE.

关键词： Internet of things

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Poster: Tancreator: A tangible tool for children to create augmented reality games

Poster: Tancreator: A tangible tool for children to create a...

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2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable computers, ISWC 2018

作者： Jin, Qiao Wang, Danli Sun, Fang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China School of Computer and Information Technology Liaoning Normal University Dalian China

ISBN: (纸本)9781450359665

In this paper, we present TanCreator, a tangible authoring tool which facilitates children to create games based on Augmented Reality (AR) and sensor technologies. Combining AR elements and sensors in games bridges virtual world with realistic surroundings closely together, providing more joyful and intuitive creating experiment for children. Children could boost their creativity via creating their own maze games in daily life with paper tokens and sensors. It is also great training for children's motor skills such as hand-eye coordination. © 2018 Copyright is held by the owner/author(s).

关键词： Augmented reality

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A concept of an agent-augmented process automation system

A concept of an agent-augmented process automation system

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IEEE International Symposium on Intelligent Control (ISIC)

作者： I. Seilonen P. Appelqvist M. Vainio A. Halme K. Koskinen Information and Computer Systems in Automation Helsinki University of Technology Finland Automation Technology Laboratory Helsinki University of Technology HUT Finland

This paper studies issues concerning the application of agent technology to process automation systems. We present an approach to achieve increased flexibility and fault-tolerance in process control operations, as well as enhanced systems configuration and maintenance. A functional specification of an agent based system as an extension to traditional process automation systems is described. The software architecture for the implementation of the required functionality is also presented. Furthermore, the connection of a novel type of mobile instrumentation to this concept is presented.

关键词： Process control Robotics and automation Instruments Automatic control Application software Design automation Laboratories Software architecture Fault tolerance Mobile robots

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Guest Editorial Introduction to the Special Issue on Large-Scale Video Analytics for Enhanced Security: Algorithms and systems

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IEEE Transactions on systems, Man, and Cybernetics: systems 2017年第4期47卷 589-592页

作者： Huang, Kaiqi Tan, Tieniu Maybank, Steve Chellappa, Rama Aggarval, Jake Institute of Automation Chinese Academy of Sciences Beijing100049 China Department of Computer Science and Information Systems University of London LondonWC1E7HX United Kingdom Department of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Department of Electrical and Computer Engineering University of Texas AustinTX78712 United States

Due to the rapid increase of the number of cameras used in the video surveillance and the huge needs of the smart city and public security, video surveillance by human beings is no longer suitable. Hence, since the end of the last century, video analytics for security or visual surveillance has become one of the hottest research topics. Wide-area video surveillance systems can have extremely high data rates and high data volumes. Therefore, the challenge of video analytics is to extract meaningful information efficiently from the huge flow of video data in order to produce high-level semantic descriptions of the activities occurring in the area under surveillance.

关键词： Special issues and sections Security Algorithm design and analysis Surveillance Visual analytics

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Smart Manufacturing Integration of Heterogeneous information systems via OPC UA. A Case Study

Smart Manufacturing Integration of Heterogeneous Information...

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2024 International Conference Automatics and Informatics, ICAI 2024

作者： Vasilev, Plamen Boneva, Ani Ivanova, Veronika Tsvetanov, Tsetso University of Chemical Technology and Metallurgy Department of Industrial Automation Sofia Bulgaria Institute of Information and Communication Technologies Bulgarian Academy of Sciences Department of Communication and Computer Systems Sofia Bulgaria Institute of Robotics Bulgaria Academy of Sciences Department of Robotized and Mechatronics Intelligent Systems Sofia Bulgaria

ISBN: (纸本)9798350353907

Modern automation, digitalization, virtualization, and intelligent production impose new criteria and approaches to process management. The operation and performance of any system and device depend on how it is managed. The article describes Smart Manufacturing Integration of Heterogeneous information systems via OPC UA. The main goal is the development of heterogeneous information systems with real applications, with which reliable and up-to-date information can be exchanged between systems of different hierarchical levels. The goal was achieved with the following steps i) building the research infrastructure ii) analyzing the information compatibility and challenges in integrating systems from different hierarchical levels, and iii) implementing the integration by means of the OPC-UA standard communication protocol. The setup has been tested under laboratory conditions. The obtained results are shown. © 2024 IEEE.

关键词： Smart manufacturing

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Multi-agent based information access services for condition monitoring in process automation

Multi-agent based information access services for condition ...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： T. Pirttioja A. Pakonen I. Seilonen A. Halme K. Koskinen Automation Technology Laboratory Helsinki University of Technology Finland VTT Industrial Systems Espoo Finland Information and Computer Systems in Automation Helsinki University of Technology Finland

This paper studies issues concerning the application of goal-oriented information agents to condition monitoring tasks in process automation. In the presented approach, an agent-based information access layer is operating as a mediator for various types of process-related information. The agent system may be seen as an active partner for human users in this information intensive application domain. In the future, more and more automation related information will be available in electronic form. Physical sensors provide not only measurements but also reliability information, and numerous configuration details are available in electronic form. The challenge is to integrate as much of the available information as possible, and to automate the processing of this information to enable easy decision-making for end users.

关键词： Condition monitoring automation Humans Paper technology Laboratories computer industry Application software Decision making computerized monitoring Ontologies

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Web-applications Fault Tolerance and Autoscaling Provided by the Combined Method of Databases Scaling 12

Web-applications Fault Tolerance and Autoscaling Provided by...

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12th International Conference on Advanced computer information Technologies, ACIT 2022

作者： Korobeinikova, Tetiana Maidaniuk, Volodymyr Romanyuk, Olexandr Chekhmestruk, Roman Romanyuk, Oksana Romanyuk, Sergey Institute of Computer Technologies Automation and Metrology Lviv Polytechnic National University Lviv Ukraine Vinnytsia National Technical University Faculty of Information Technologies and Computer Engineering Vinnytsia Ukraine 3D Generation Ua Vinnitsa Ukraine Institute of Computer Systems Odessa Polytechnic State University Odessa Ukraine

The purpose of this work is to accelerate the server applications operation at high load and to automate the server systems scaling processes, which allows to reduce the cost of infrastructure and its maintenance. ... 详细信息

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

关键词： Database systems

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Sustainable Mining in the Era of Artificial Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 1-4页

作者： Long Chen Yuting Xie Yutong Wang Shirong Ge Fei-Yue Wang IEEE the State Key Laboratory for Management and Control of Complex Systems at the Institute of Automation Chinese Academy of SciencesBeijing 100190China the National Laboratory of Pattern Recognition at the Institute of Automation and Waytous Ltd.China the School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 510275GuangdongChina the School of Mechanical Electronic and Information Engineering China University of Mining and Technology BeijingBejing 100083China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread ***-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

关键词： Sustainable mining consequences

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Using a Combination of LiDAR, RADAR, and Image Data for 3D Object Detection in Autonomous Vehicles 11

Using a Combination of LiDAR, RADAR, and Image Data for 3D O...

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11th Annual IEEE information Technology, Electronics and Mobile Communication Conference, IEMCON 2020

作者： Sahba, Ramin Sahba, Amin Sahba, Farshid University of Texas at San Antonio Department of Electrical and Computer Engineering Department of Information Systems and Cyber Security San AntonioTX United States Institute for Informatics and Automation Problems National Academy of Sciences of Armenia Yerevan Armenia

ISBN: (纸本)9781728184166

One of the topics that is highly regarded and researched in the field of artificial intelligence and machine learning is object detection. Its use is especially important in autonomous vehicles. The various methods used to detect objects are based on different types of data, including image, radar, and lidar. Using a point clouds is one of the new methods for 3D object detection proposed in some recent work. One of the recently presented efficient methods is PointPillars network. It is an encoder that can learn from data available in a point cloud and then organize it as a representation in vertical columns (pillars). This representation can be used for 3D object detection. in this work, we try to develop a high performance model for 3D object detection based on PointPillars network exploiting a combination of lidar, radar, and image data to be used for autonomous vehicles perception. We use lidar, radar, and image data in nuScenes dataset to predict 3D boxes for three classes of objects that are car, pedestrian, and bus. To measure and compare results, we use nuScenes detection score (NDS) that is a combined metric for detection task. Results show that increasing the number of lidar sweeps, and combining them with radar and image data, significantly improve the performance of the 3D object detector. We suggest a method to combine different types of input data (lidar, radar, image) using a weighting system that can be used as the input for the encoder. © 2020 IEEE.

关键词： Object detection

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