Pub Date : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00031
H. Zhang, Sande Wang, Tongkui Yu, Bo Zhang, Jin Lin, Yanqiong Liu
With the rapid development of weapons and equipment, the noise of naval weapons and equipment such as ships and submarines in various countries has been controlled to a very low level. Because the current spectrum analysis method has limited ability to analyze and process such signals, this puts higher requirements on our target detection and recognition technology. Based on the advantages of autoregressive method in signal processing and high resolution, and compatible with parametric methods, this paper studies the application of AR model in the identification and analysis of noise sources of transient noise, and establishes a short-time high resolution spectral analysis method based on autoregressive model. And through the simulation and analysis of the known component transient noise signal and the actual transient noise test data analysis of the real ship, the method can accurately obtain the transient noise generation time and characteristic spectrum, which has strong application value in terms of engineering.
{"title":"Research on Transient Noise Analysis Method of Ship Based on AR Model","authors":"H. Zhang, Sande Wang, Tongkui Yu, Bo Zhang, Jin Lin, Yanqiong Liu","doi":"10.1109/ICVISP54630.2021.00031","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00031","url":null,"abstract":"With the rapid development of weapons and equipment, the noise of naval weapons and equipment such as ships and submarines in various countries has been controlled to a very low level. Because the current spectrum analysis method has limited ability to analyze and process such signals, this puts higher requirements on our target detection and recognition technology. Based on the advantages of autoregressive method in signal processing and high resolution, and compatible with parametric methods, this paper studies the application of AR model in the identification and analysis of noise sources of transient noise, and establishes a short-time high resolution spectral analysis method based on autoregressive model. And through the simulation and analysis of the known component transient noise signal and the actual transient noise test data analysis of the real ship, the method can accurately obtain the transient noise generation time and characteristic spectrum, which has strong application value in terms of engineering.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123164785","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00026
Qi Kong, Liangliang Zhang, Xin Xu
Vehicle localization is an important problem in autonomous driving research. Main stream methods use sensors on the vehicle with a SLAM algorithm, yet it has disadvantage on safety, cost and global intelligence comparing to sensing from infrastructure, especially surveillance cameras which are already pervasive in public urban area. To better address these challenges, this paper, for the first time, uses multiple surveillance cameras for vehicle localization. In this paper, a flexible two-stage framework for vehicle localization with surveillance cameras is introduced. Flexible deploying is its advantage. With first stage deploying on the camera local computing and second stage on the cloud, it can runs on limited bandwidth and computing conditions. Two potential directions of solutions under the framework are proposed. One is using instance mask as intermediate information, another is using key points of the vehicle.
{"title":"Vehicle Localization with Surveillance Cameras","authors":"Qi Kong, Liangliang Zhang, Xin Xu","doi":"10.1109/ICVISP54630.2021.00026","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00026","url":null,"abstract":"Vehicle localization is an important problem in autonomous driving research. Main stream methods use sensors on the vehicle with a SLAM algorithm, yet it has disadvantage on safety, cost and global intelligence comparing to sensing from infrastructure, especially surveillance cameras which are already pervasive in public urban area. To better address these challenges, this paper, for the first time, uses multiple surveillance cameras for vehicle localization. In this paper, a flexible two-stage framework for vehicle localization with surveillance cameras is introduced. Flexible deploying is its advantage. With first stage deploying on the camera local computing and second stage on the cloud, it can runs on limited bandwidth and computing conditions. Two potential directions of solutions under the framework are proposed. One is using instance mask as intermediate information, another is using key points of the vehicle.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129989309","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00020
J. Kuklova, M. Matowicki
Congestions in peak hours is a phenomenon which is faced by many cities in the world. One of the goals of Smart City concept is to mitigate them and thus increase the level of driving comfort. The goal of this study was to determine the most significant parameters and understand which aspects are important for driving comfort. In the performed experiment, drivers with different socio-demographic characteristics and different driving experience observed the peak-hour and off-peak traffic How from drivers’ perspective and provided a subjective evaluation of driving comfort. The evaluation was then confronted to the observed traffic parameters which were either observed at place, or obtained from traffic detectors at the time when videos were recorded. It was found that immediate presence of heavy vehicles, light conditions or road geometry are parameters which can affect the level of comfort perceived by drivers just as instantaneous speed does. The findings from this study could improve the determination of traffic Level of Service and contribute to better understanding of this parameter by drivers.
{"title":"Parameters Influencing the Subjective Evaluation of Traffic Stream by Drivers","authors":"J. Kuklova, M. Matowicki","doi":"10.1109/ICVISP54630.2021.00020","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00020","url":null,"abstract":"Congestions in peak hours is a phenomenon which is faced by many cities in the world. One of the goals of Smart City concept is to mitigate them and thus increase the level of driving comfort. The goal of this study was to determine the most significant parameters and understand which aspects are important for driving comfort. In the performed experiment, drivers with different socio-demographic characteristics and different driving experience observed the peak-hour and off-peak traffic How from drivers’ perspective and provided a subjective evaluation of driving comfort. The evaluation was then confronted to the observed traffic parameters which were either observed at place, or obtained from traffic detectors at the time when videos were recorded. It was found that immediate presence of heavy vehicles, light conditions or road geometry are parameters which can affect the level of comfort perceived by drivers just as instantaneous speed does. The findings from this study could improve the determination of traffic Level of Service and contribute to better understanding of this parameter by drivers.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126791726","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00053
Fangxin Chen, K. Hu, Yupeng Yang, C. Ying, Yanhui Liu, T. Guo, Qian Meng, Daguang Han
The pipeline system in large-scale factories integrates multiple sub-systems such as power, lighting and lire control. In the traditional acceptance of measurement results for completion, the large number of cross-subsystems makes their expression not intuitive and poor interpretation and can no longer meet the requirements of inspection and later operation maintenance management of digital factories. In view of this situation, taking a workshop of FAW Volkswagen as an example, A new three-dimensional contrast detection technology is proposed in this paper. Through three-dimensional laser scanning technology, the actual data acquisition of pipelines in the workshop is carried out. This technology can provide truthful and reliable basic data information for later operation maintenance management and plant expansion.
{"title":"Study on the Application of 3-D Laser Scanning BIM Technology in Optimization and Adjustment of Factory Pipeline System","authors":"Fangxin Chen, K. Hu, Yupeng Yang, C. Ying, Yanhui Liu, T. Guo, Qian Meng, Daguang Han","doi":"10.1109/ICVISP54630.2021.00053","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00053","url":null,"abstract":"The pipeline system in large-scale factories integrates multiple sub-systems such as power, lighting and lire control. In the traditional acceptance of measurement results for completion, the large number of cross-subsystems makes their expression not intuitive and poor interpretation and can no longer meet the requirements of inspection and later operation maintenance management of digital factories. In view of this situation, taking a workshop of FAW Volkswagen as an example, A new three-dimensional contrast detection technology is proposed in this paper. Through three-dimensional laser scanning technology, the actual data acquisition of pipelines in the workshop is carried out. This technology can provide truthful and reliable basic data information for later operation maintenance management and plant expansion.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132161405","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}
International trade brings more and more attention to the public. Understanding the trade behaviour is essential for the policy makers as well as business leaders for decision making. Since the trade events are numerous and complex, it is challenging for people to catch up with the trade transactions let alone decision making. This paper applies the visualization techniques to show the trade trends and behaviours. With the visualization interface, it is much clear to understand the international trade and catch the significant trends. In addition, we also analyse the behaviour via mathematical modelling and data mining techniques. Our work assists a lot for government and business leaders to discover the trade patterns and make decisions.
{"title":"Visual Analytics for the International Trade","authors":"Haowen Jiang, Jiadong Shen, Qi-Feng Chou, Ziling Dong, Shenghui Cheng","doi":"10.1109/ICVISP54630.2021.00059","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00059","url":null,"abstract":"International trade brings more and more attention to the public. Understanding the trade behaviour is essential for the policy makers as well as business leaders for decision making. Since the trade events are numerous and complex, it is challenging for people to catch up with the trade transactions let alone decision making. This paper applies the visualization techniques to show the trade trends and behaviours. With the visualization interface, it is much clear to understand the international trade and catch the significant trends. In addition, we also analyse the behaviour via mathematical modelling and data mining techniques. Our work assists a lot for government and business leaders to discover the trade patterns and make decisions.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129692429","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00045
Zenjie Li, B. Norton
With increasing physical threats in recent years targeted at critical infrastructures, it is crucial to establish a reliable threat monitoring system integrating video surveillance and digital sensors based on cutting-edge technologies. A physical threat monitoring solution unifying the floorplan, cameras, and sensors for smart buildings has been set up in our study. Computer vision and deep learning models are used for video streams analysis. When a threat is detected by a rule engine based on the real-time analysis results combining with feedback from related digital sensors, an alert is sent to the Video Management System so that human operators can take further action.A physical threat monitoring system typically needs to address complex and even destructive incidents, such as fire, which is unrealistic to simulate in real life. Restrictions imposed during the Covid-19 pandemic and privacy concerns have added to the challenges. Our study utilises the Unreal Engine to simulate some typical suspicious and intrusion scenes with photorealistic qualities in the context of a virtual building. Add-on programs are implemented to transfer the video stream from virtual PTZ cameras to the Milestone Video Management System and enable users to control those cameras from the graphic client application. Virtual sensors such as fire alarms, temperature sensors and door access controls are implemented similarly, fulfilling the same programmatic VMS interface as real-life sensors. Thanks to this simulation system’s extensibility and repeatability, we have consolidated this unified physical threat monitoring system and verified its effectiveness and user-friendliness. Both the simulated Unreal scenes and the software add-ons developed during this study are highly modulated and thereby are ready for reuse in future projects in this area.
{"title":"Unified Physical Threat Monitoring System Aided by Virtual Building Simulation","authors":"Zenjie Li, B. Norton","doi":"10.1109/ICVISP54630.2021.00045","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00045","url":null,"abstract":"With increasing physical threats in recent years targeted at critical infrastructures, it is crucial to establish a reliable threat monitoring system integrating video surveillance and digital sensors based on cutting-edge technologies. A physical threat monitoring solution unifying the floorplan, cameras, and sensors for smart buildings has been set up in our study. Computer vision and deep learning models are used for video streams analysis. When a threat is detected by a rule engine based on the real-time analysis results combining with feedback from related digital sensors, an alert is sent to the Video Management System so that human operators can take further action.A physical threat monitoring system typically needs to address complex and even destructive incidents, such as fire, which is unrealistic to simulate in real life. Restrictions imposed during the Covid-19 pandemic and privacy concerns have added to the challenges. Our study utilises the Unreal Engine to simulate some typical suspicious and intrusion scenes with photorealistic qualities in the context of a virtual building. Add-on programs are implemented to transfer the video stream from virtual PTZ cameras to the Milestone Video Management System and enable users to control those cameras from the graphic client application. Virtual sensors such as fire alarms, temperature sensors and door access controls are implemented similarly, fulfilling the same programmatic VMS interface as real-life sensors. Thanks to this simulation system’s extensibility and repeatability, we have consolidated this unified physical threat monitoring system and verified its effectiveness and user-friendliness. Both the simulated Unreal scenes and the software add-ons developed during this study are highly modulated and thereby are ready for reuse in future projects in this area.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130406487","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00062
Qi Liu, Weifeng Sun, Siyang Liu
In order to meet the demand of dual-band infrared detection, this paper presents a design scheme of medium and short wave two-color infrared focal plane readout circuit. The two-color pixel unit circuit and operating mode switching circuit are mainly designed, and finally designed two-color infrared focal plane readout circuit chip with area 12.5 × 12.5mm2. The test results show that the chip designed in this paper realizes the function of two-color readout and obtains good imaging effect The output swing range is 1.55~4.7V, the output frame frequency can reach 60Hz, the maximum power consumption is less than 200mW, and the dynamic range is about 79.8dB.
{"title":"Design of 320×256-30um DI Medium and Short Wave Two-color IRFPA Readout Circuit","authors":"Qi Liu, Weifeng Sun, Siyang Liu","doi":"10.1109/ICVISP54630.2021.00062","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00062","url":null,"abstract":"In order to meet the demand of dual-band infrared detection, this paper presents a design scheme of medium and short wave two-color infrared focal plane readout circuit. The two-color pixel unit circuit and operating mode switching circuit are mainly designed, and finally designed two-color infrared focal plane readout circuit chip with area 12.5 × 12.5mm2. The test results show that the chip designed in this paper realizes the function of two-color readout and obtains good imaging effect The output swing range is 1.55~4.7V, the output frame frequency can reach 60Hz, the maximum power consumption is less than 200mW, and the dynamic range is about 79.8dB.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115377793","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00016
YuluLaura Lin, J. Guan
This paper draws from people’s choices of different services in autonomous vehicles to generate new insights about their acceptance of autonomous vehicles to meet their mobility needs. This article highlights the relationship between people’s mindfulness and their choice of the following applications of autonomous driving technology: self-driving-uber, car-sharing (Car2go), subway/rail, rental car, paratransit, self-owned autonomous car, self-driving car subscription, and self-driving bus. A quantitative analysis shows that in Chinese metropolitan areas, mindful people’s trust, health situations, travel costs, knowledge of autonomous vehicles, and their willingness to change their travel mode are significantly related to their choosing autonomous paratransit as their preferred mode. Travel costs have a significant positive effect on participants’ preference for autonomous vehicles, while income shows a significant negative impact. These findings indicate that using shared autonomous vehicles in paratransit services can improve high travel costs and low-income people’s trust in autonomous vehicles.
{"title":"Mindful People’s preference for Different Services of Autonomous Vehicles in China","authors":"YuluLaura Lin, J. Guan","doi":"10.1109/ICVISP54630.2021.00016","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00016","url":null,"abstract":"This paper draws from people’s choices of different services in autonomous vehicles to generate new insights about their acceptance of autonomous vehicles to meet their mobility needs. This article highlights the relationship between people’s mindfulness and their choice of the following applications of autonomous driving technology: self-driving-uber, car-sharing (Car2go), subway/rail, rental car, paratransit, self-owned autonomous car, self-driving car subscription, and self-driving bus. A quantitative analysis shows that in Chinese metropolitan areas, mindful people’s trust, health situations, travel costs, knowledge of autonomous vehicles, and their willingness to change their travel mode are significantly related to their choosing autonomous paratransit as their preferred mode. Travel costs have a significant positive effect on participants’ preference for autonomous vehicles, while income shows a significant negative impact. These findings indicate that using shared autonomous vehicles in paratransit services can improve high travel costs and low-income people’s trust in autonomous vehicles.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127351004","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00033
Lubna Eljabu, Mohammad Etemad, S. Matwin
One of the critical applications of trajectory mining is Event Detection, where an automatized task identifies the deviation of a vessel’s movement from its standard route. Conventionally, Origin-Destination matrix data is utilized for event detection which has limitations such as removal of temporal aspect of data and inability to access to trajectory features such as speed of vessel from origin to destination. To utilize aforementioned features available in Automatic information system (AIS), we formulate the problem in a novel way, by detecting anomalies in a set of directed graphs representing the movement pattern at each time interval. We further propose Graph Network Deviation Detector (GNDD), which leverages graph embedding and context embedding techniques to capture anomalies in the spatio-temporal patterns of movement. Extensive experiments applied on five real-world AIS datasets show that our method achieved promising results in identifying abnormal movements.
{"title":"Anomaly Detection in Maritime Domain based on Spatio-Temporal Analysis of AIS Data Using Graph Neural Networks","authors":"Lubna Eljabu, Mohammad Etemad, S. Matwin","doi":"10.1109/ICVISP54630.2021.00033","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00033","url":null,"abstract":"One of the critical applications of trajectory mining is Event Detection, where an automatized task identifies the deviation of a vessel’s movement from its standard route. Conventionally, Origin-Destination matrix data is utilized for event detection which has limitations such as removal of temporal aspect of data and inability to access to trajectory features such as speed of vessel from origin to destination. To utilize aforementioned features available in Automatic information system (AIS), we formulate the problem in a novel way, by detecting anomalies in a set of directed graphs representing the movement pattern at each time interval. We further propose Graph Network Deviation Detector (GNDD), which leverages graph embedding and context embedding techniques to capture anomalies in the spatio-temporal patterns of movement. Extensive experiments applied on five real-world AIS datasets show that our method achieved promising results in identifying abnormal movements.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127882390","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 : 2021-12-01DOI: 10.1109/ICVISP54630.2021.00046
Boudjit Kamel, Ammi Oussama
In recent years, thanks to the low cost of deploying, maintaining an Unmanned Aerial Vehicle (UAV) system and the possibility to operating them in areas inaccessible or dangerous for human pilots, UAVs have attracted much research attention in both the military field and civilian application. In order to deal with more sophisticated tasks, such as searching survival points, multiple target monitoring and tracking, the application of UAV swarms is for seen. This requires more complex control, communication and coordination mechanisms. However, these mechanisms are difficult to test and analyses under flight dynamic conditions. This paper presents recent examples from work in our research team on in incorporates leader-follower unmanned aerial vehicles using vision processing, radiofrequency data transmission. This system targets search and rescue environments, employing controls, vision processing, and embedded systems to allow for easy deployment of multiple quadrotor UAVs while requiring the control of only one. The system demonstrates a relative localization scheme for UAVs in a leader-follower configuration, allowing for predictive manoeuvres including path following.
{"title":"Cooperative Navigation and Autonomous Formation Flight for a Swarm of Unmanned Aerial Vehicle","authors":"Boudjit Kamel, Ammi Oussama","doi":"10.1109/ICVISP54630.2021.00046","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00046","url":null,"abstract":"In recent years, thanks to the low cost of deploying, maintaining an Unmanned Aerial Vehicle (UAV) system and the possibility to operating them in areas inaccessible or dangerous for human pilots, UAVs have attracted much research attention in both the military field and civilian application. In order to deal with more sophisticated tasks, such as searching survival points, multiple target monitoring and tracking, the application of UAV swarms is for seen. This requires more complex control, communication and coordination mechanisms. However, these mechanisms are difficult to test and analyses under flight dynamic conditions. This paper presents recent examples from work in our research team on in incorporates leader-follower unmanned aerial vehicles using vision processing, radiofrequency data transmission. This system targets search and rescue environments, employing controls, vision processing, and embedded systems to allow for easy deployment of multiple quadrotor UAVs while requiring the control of only one. The system demonstrates a relative localization scheme for UAVs in a leader-follower configuration, allowing for predictive manoeuvres including path following.","PeriodicalId":296789,"journal":{"name":"2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131412025","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}
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