2021 5th International Conference on Vision, Image and Signal Processing (ICVISP)最新文献_第4页

Research on Transient Noise Analysis Method of Ship Based on AR Model 基于AR模型的船舶瞬态噪声分析方法研究

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00031

H. Zhang, Sande Wang, Tongkui Yu, Bo Zhang, Jin Lin, Yanqiong Liu

引用次数: 0

Vehicle Localization with Surveillance Cameras 车辆定位与监控摄像头

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00026

Qi Kong, Liangliang Zhang, Xin Xu

引用次数: 0

Parameters Influencing the Subjective Evaluation of Traffic Stream by Drivers 影响驾驶员对交通流主观评价的参数

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00020

J. Kuklova, M. Matowicki

{"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}

引用次数: 0

Study on the Application of 3-D Laser Scanning BIM Technology in Optimization and Adjustment of Factory Pipeline System 三维激光扫描BIM技术在工厂管道系统优化调整中的应用研究

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00053

Fangxin Chen, K. Hu, Yupeng Yang, C. Ying, Yanhui Liu, T. Guo, Qian Meng, Daguang Han

引用次数: 0

Visual Analytics for the International Trade 国际贸易的可视化分析

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00059

Haowen Jiang, Jiadong Shen, Qi-Feng Chou, Ziling Dong, Shenghui Cheng

引用次数: 0

Unified Physical Threat Monitoring System Aided by Virtual Building Simulation 基于虚拟建筑仿真的统一物理威胁监控系统

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00045

Zenjie Li, B. Norton

{"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}

引用次数: 0

Design of 320×256-30um DI Medium and Short Wave Two-color IRFPA Readout Circuit 320×256-30um DI中短波双色IRFPA读出电路的设计

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00062

Qi Liu, Weifeng Sun, Siyang Liu

引用次数: 0

Mindful People’s preference for Different Services of Autonomous Vehicles in China 中国人们对自动驾驶汽车不同服务的偏好

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00016

YuluLaura Lin, J. Guan

{"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}

引用次数: 0

Anomaly Detection in Maritime Domain based on Spatio-Temporal Analysis of AIS Data Using Graph Neural Networks 基于AIS数据时空分析的图神经网络海事异常检测

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00033

Lubna Eljabu, Mohammad Etemad, S. Matwin

引用次数: 5

DRSTNet: A Robust Spatio-temporal Network with Dilated Residual Convolutions for Lane Detection DRSTNet:用于车道检测的扩展残差卷积鲁棒时空网络

2021 5th International Conference on Vision, Image and Signal Processing (ICVISP) Pub Date : 2021-12-01 DOI: 10.1109/ICVISP54630.2021.00018

Jiyong Zhang, T. Deng, Fei Yan, Wenbo Liu

{"title":"DRSTNet: A Robust Spatio-temporal Network with Dilated Residual Convolutions for Lane Detection","authors":"Jiyong Zhang, T. Deng, Fei Yan, Wenbo Liu","doi":"10.1109/ICVISP54630.2021.00018","DOIUrl":"https://doi.org/10.1109/ICVISP54630.2021.00018","url":null,"abstract":"Lane detection plays a more and more significant role in ensuring the safety of autonomous driving, Lane Departure Warning, etc. Although a lot of research has been conducted with innovative methods on lane detection, pursuing the high accuracy of lane detection in challenging scenarios is still an open research question. In this work, we present a robust lane detection model via dilated residual convolutions and spatio-temporal networks (DRSTNet). The dilated residual convolutions make our model have the ability to obtain richer and denser feature information by expanding the receptive fields of the convolutions, and provide our model with necessary supplements by skip connections. In addition, the spatio-temporal networks further enhance the learning ability of our model in extracting effective features by dealing with spatial and temporal information via convolutional gated recurrent units (ConvGRUs). Furthermore, a large number of experiments verify that our model outperforms the state-of-the-art algorithms while increasing the robustness and reducing the size of the weight parameter, achieving 81.35% on DET and 73.0% on CULane.","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":"129520867","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}

引用次数: 0