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vision Belt: Intelligent Assistive Device for Collision Avoidance by Using computer vision technology and Ultrasonic Sensors 11

Vision Belt: Intelligent Assistive Device for Collision Avoi...

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11th IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan) - Empower of Innovative Consumer technology

作者： Hung, Chi-Huang Chi, Chun-Nan Huang, Shih-Yung Hsu, Chia-Hsun Lu, Yi-An Fu Jen Catholic Univ Lee Ming Inst Technol Dept Informat Technol Grad Inst Appl Sci & Engn New Taipei Taiwan Fu Jen Catholic Univ Grad Inst Appl Sci & Engn New Taipei Taiwan Kang Chiao Int Sch Dept Int High Sch New Taipei Taiwan Lee Ming Inst Technol Dept Elect Engn New Taipei Taiwan

ISBN: (纸本)9798350386851;9798350386844

Visually impaired individuals have been using white canes for walking on the road for many years. Although they are affordable and easy to use, there are still shortcomings in terms of providing sufficient reminders and warnings. While tactile paving on the floor provides a guide for visually impaired individuals to follow, they must walk on it with great concentration. The drawback is that sometimes it can lead to tripping or missing directional cues. White canes may not always offer sufficient assistance to those with limited abilities. Therefore, this study utilizes a miniature camera and embedded computer with computer vision technology to create a belt assistance system. This system helps visually impaired individuals walk on yellow tactile paving, and when combined with ultrasonic sensors, it extends the detection range from 2D to 3D. In this way, visually impaired individuals can understand whether there are obstacles ahead and if they are on the correct path through vibrations from left and right vibrating motors.

关键词： Obstacle Avoidance Visually Impaired Person Auxiliary Equipment Ultrasonic computer vision technology

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Design and implementation of football training system based on computer vision technology 7

Design and implementation of football training system based ...

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7th International Conference on Electronic Information technology and computer Engineering (EITCE)

作者： Gao, Hongfei Meng, Shasha Ma, Shaowen Chongqing Three Gorges Vocat Coll Chongqing 404100 Peoples R China

ISBN: (纸本)9798400708305

In order to improve the science and quality of football training, a football training system based on computer vision technology is studied. Collect initial motion data through motion capture to form an action database, modify and design the actions in the action database, obtain standard technical actions, and arrange and simulate each standard technical action through motion splicing;By using video shooting technology to obtain the image data of athletes during physical exercise, the measurement deviation in sports training is discussed through the trajectory tracking and error judgment of the motion nodes, so as to provide more efficient sports guidance and improve the movement and training level. The simulation test results show that compared with other corresponding systems, the system is outstanding in the aspects of fast response and improved control accuracy, so as to realize the optimal monitoring effect of sports training errors.

关键词： Sports training computer vision technology Image processing

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3D Scene Object Perception Algorithm Based on computer vision technology Based on Multi-View 1

3D Scene Object Perception Algorithm Based on Computer Visio...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Chen, Yihua University of Science and Technology of China Anhui Hefei China

ISBN: (纸本)9798350316469

Traditional single-viewpoint algorithms have limitations in target perception in 3D scenes, while computer vision technology based on multi-viewpoints can provide more comprehensive and accurate target perception capabilities. This study proposes a multi-view computer vision technology based object perception algorithm for 3D scenes. In this paper, image data from multiple angles is used for target positioning and shape reconstruction, and the accuracy of target position and shape is improved by combining information from different angles. Synthesize information from multiple angles to obtain more comprehensive and richer target semantic information. Through experiments and evaluations on real 3D scene datasets, the algorithm in this paper achieves remarkable research results. After experimental testing, the recall rate of the algorithm in this paper ranges from 81% to 88%. Compared with traditional single-viewpoint algorithms, multi-viewpoint-based algorithms show higher accuracy and comprehensiveness in object localization, shape reconstruction and semantic understanding. © 2023 IEEE.

关键词： 3D Scene Perception 3D Target Recognition computer vision technology Target Perception Algorithm

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Recognition Method for Building Restoration Images Based on computer vision technology

Recognition Method for Building Restoration Images Based on ...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Yu, Chen Wu, Kun Shenzhen University School Architeture & Urban Planning Shenzhen China

ISBN: (纸本)9798350313413

Building Inpainting technology can complete the lost part of the building image or remove the polluted part of the image from the true *** vision (CV) technology is a part of the field of artificial intelligence, which has three-dimensional analysis capabilities and can analyze the data information in images, achieving true 'recognition' and 'understanding of images'. Applying it to building image recognition and restoration has great advantages. To address the issues of traditional Inpainting technology, this paper studied CV technology and image recognition and restoration technology, aiming to apply CV technology to building image recognition and restoration. The practice proved that the comprehensive score of building image recognition and restoration using CV technology according to the index was 94.65 on average, 18.85 points higher than the traditional Inpainting method, which proves that the method designed in this article is really effective and that the utilization of CV technology to the analysis and recognition of building Inpainting plays a very significant role. © 2023 IEEE.

关键词： 3D analysis ability building image recognition computer vision technology inpainting technology

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Research on Human Motion Recognition Based on computer vision technology 2022

Research on Human Motion Recognition Based on Computer Visio...

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5th International Conference on Machine vision and Applications (ICMVA)

作者： Sun, Jie Jianghan Univ Sch Phys Educ Wuhan 430056 Hubei Peoples R China

ISBN: (纸本)9781450395670

In order to improve the accuracy of human motion recognition, computer vision technology is selected as the research tool, and a representation method of human bone and joint is proposed. This method takes the adaptive human motion bone center architecture as the action recognition tool, constructs the human motion action recognition model by calculating the angular acceleration and angular velocity of the neck and hip joints, and uses the model to calculate the action data and generate the recognition results. The experimental results show that the motion recognition accuracy of this algorithm is high, and it can be used as a motion recognition tool.

关键词： action recognition computer vision technology Bone Center

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Enhancing urban real-time PM2.5 monitoring in street canyons by machine learning and computer vision technology

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SUSTAINABLE CITIES AND SOCIETY 2024年 100卷

作者： Fan, Zhiguang Zhao, Yuan Hu, Baicheng Wang, Li Guo, Yuxuan Tang, Zhiyuan Tang, Junwen Ma, Jianmin Gao, Hong Huang, Tao Mao, Xiaoxuan Lanzhou Univ Coll Earth & Environm Sci Key Lab Environm Pollut Predict & Control Lanzhou 730000 Gansu Peoples R China Lanzhou Univ Collaborat Innovat Ctr Western Ecol Safety Lanzhou 730000 Peoples R China Peking Univ Coll Urban & Environm Sci Lab Earth Surface Proc Beijing 100871 Peoples R China

During peak hours, both pedestrians and drivers face extended exposure to road air pollution, raising the risk of respiratory diseases. Variations in traffic volume, building attributes, and weather conditions in street canyons lead to differing exposure levels across road sections and intersections. Though deploying numerous sensors provides real-time access to PM2.5 levels in each road section, they cannot interpret the impact of weather, traffic, and buildings on these levels. Therefore, in Lanzhou City, we attempted to use computer vision technology (CVT) to extract real-time traffic volume and street-view features from traffic images for PM2.5 concentration prediction, and to interpret the impact of road environment changes on PM2.5 levels. Results show that by using the Extreme Gradient Boosting (XGB) regression model, the coefficient of determination for PM2.5 prediction reaches R2=0.956. Meteorological conditions, traffic volume, and buildings are key variables in predicting road PM2.5 concentrations. Meteorological conditions control the continuous fluctuation of road PM2.5 levels, while traffic volume can lead to sudden changes in PM2.5 levels. The research indicates that the combination of traffic cameras and CVT can acquire road PM2.5 concentrations, contributing significantly to rapidly understanding road pollution status, identifying highly polluted roads, and conducting exposure assessments of roadways.

关键词： PM2.5 Urban roads Street view Traffic image computer vision technology Extreme gradient boosting

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Image acquisition based on computer vision technology for optimizing thermal energy in building environments and simulating VR interior design

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2024年 55卷

作者： Zhang, Hui Sanjiang Univ Coll Art Nanjing 210012 Jiangsu Peoples R China

With the acceleration of urbanization, the problem of building energy consumption has become increasingly prominent, and the construction of low energy consumption and high comfort building environment has become a hot research field. The purpose of this study is to explore the use of computer vision technology for image acquisition, optimize the thermal energy management in the building environment through intelligent analysis, and improve the energy efficiency and comfort of interior design. Through the establishment of image acquisition system based on computer vision, the indoor and outdoor environment is monitored in real time. A deep learning algorithm is used to process the acquired images and extract the thermal energy characteristics of the buildings. Combined with virtual reality (VR) technology, a 3D model of interior design was constructed to simulate the impact of different design schemes on energy consumption. The experimental results show that the real-time data obtained by computer vision technology can effectively identify the heat energy distribution in the building, and provide optimization suggestions for interior design. Simulation results of different design options show that the optimized design reduces energy consumption while improving occupant comfort. Therefore, computer vision technology shows a good application prospect in the thermal energy optimization of building environment. By combining VR interior design simulation, the technology not only improves the accuracy of thermal management, but also provides architects with more information-based decision support and promotes the development of smart buildings.

关键词： computer vision technology Image acquisition Building environmental heat energy optimization VR interior design simulation

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Intelligent Monitoring and Management of Trade Logistics Based on Big Data and computer vision technology

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Procedia computer Science 2024年 243卷 700-707页

作者： Zhongpo Gao Chengwen Kang Xufeng Wu School of Economics Harbin University of Commerce Harbin 150028 China School of Economics and Management Harbin University Harbin 150086 China

Technologies such as big data and computer vision are increasingly being applied in trade logistics, and their integration provides strong support for achieving modernization and intelligence in the logistics industry. This article utilizes various sensors, global positioning systems, radio frequency identification and other technologies to obtain real-time information on the location, temperature, and transportation status of goods. Video surveillance and image recognition methods can be used, combined with computer vision technology, to monitor the loading and unloading process of goods and the condition of transportation vehicles in real time. This article studies an intelligent monitoring algorithm that achieves anomaly detection, warning prompts, and ensures the safety and smoothness of transportation. Exploration of transportation path optimization in batch 1 experimental group (big data analysis) saved 3 hours of time and cost by 500 yuan. This article explores the intelligent monitoring and management of trade logistics based on big data and computer vision technology, which can help improve transportation efficiency and reduce costs.

关键词： Intelligent Monitoring Of Trade Logistics Big Data computer vision technology Transportation Path Optimization

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Research progress of computer vision technology in abnormal fish detection

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AQUACULTURAL ENGINEERING 2023年第1期103卷

作者： Liu, Chunhong Wang, Zhiyong Li, Yachao Zhang, Zhenzuo Li, Jiawei Xu, Chen Du, Rongxiang Li, Daoliang Duan, Qingling China Agr Univ Natl Innovat Ctr Digital Fishery Beijing 100083 Peoples R China China Agr Univ Key Lab Smart Farming Technol Aquat Anim & Livesto Minist Agr & Rural Affairs Beijing 100083 Peoples R China Beijing Engn & Technol Res Ctr Internet Things Agr Beijing Peoples R China China Agr Univ Coll Informat & Elect Engn Beijing 100083 Peoples R China Laizhou Jinyiyuan Aquat Prod Co Ltd Laizhou 261418 Shandong Peoples R China

Abnormal fish detection helps producers adjust breeding strategies in a timely manner to prevent the occurrence of diseases and improve aquaculture efficiency and quality. The rapid development of computer vision tech-nology provides a noninvasive method for abnormal fish detection, which can be used to identify and classify abnormal fish. This paper provides an overview of the research progress of computer vision techniques in detecting abnormal fish over the past two decades. For the first time, the abnormal fish detection task is divided into three external manifestations: abnormal physiological activities, abnormal trajectories, and abnormal sur-face features of fish. The traditional methods and deep learning methods in computer vision technology are further summarized for their application approaches in these three research types, and the commonly used classical algorithm models in abnormal fish detection are introduced comprehensively. In addition, this paper summarizes several common methods for obtaining public datasets in aquaculture and evaluation indicators of model accuracy, emphasizing two methods for researchers to collect experimental on-site data. Finally, based on the above work, this paper analyzes several challenges in abnormal fish detection, proposes feasible strategies for each challenge, and notes the importance of improving models to effectively integrate and analyze data from multiple platforms. This paper provides some reference value for research on abnormal fish.

关键词： computer vision technology Deep learning Abnormal physiological activities Abnormal trajectories Abnormal surface features

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Application of Chaos Cuckoo Search Algorithm in computer vision technology

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SOFT COMPUTING 2021年第18期25卷 12373-12387页

作者： Fan, Jiayi Xu, Wenjing Huang, Yi Samuel, R. Dinesh Jackson Jiangsu Univ Sci & Technol Sch Elect & Informat Technol Suzhou Inst Technol Zhangjiagang 215600 Peoples R China Zhangjiagang City Investment Co Ltd Engn Management Dept Zhangjiagang 215600 Peoples R China Oxford Brookes Univ Visual Artificial Intelligence Lab Fac Technol Design & Environm Oxford England

Image segmentation is an essential phase in image analysis and computer vision. In computer vision, image processing denotes the analysis and handling of digital images to enhance their quality. Image processing becomes more challenging because of many complexes, noisy images from various sources in selecting applications, requiring minimal computational time/cost procedures and higher accuracy. Hence, in this paper, Chaos Cuckoo Search Algorithm (CCSA) has been suggested to resolve image segmentation and improve image accuracy. An un-deterministic problem is the challenge of unsure pixel detection and rim formulation for picture segmentation. The use of CV and optimization approaches has reduced the uncertainty about restricted picture characteristics. Ergodicity and stochasticity are formulated in this proposal which fulfill certain pixel and edge detection. Heterogeneous picture patterns solve the insecurity with chaotic maps and an Algorithm of Cuckoo Search. Unlike ordinary cuckoo searches, the chaotic mapping fuses deterministic search and stochastic validations. Chaos belongs to a characteristic of nonlinear models. Chaotic motion ensures homogeneity within a certain range since it has obsessed ergodicity, uncertainty, and stochasticity. The proposed model automates algorithms' settings and delivers optimal parameters for computer vision applications and image segmentation. Furthermore, a local search approach is utilized to enhance the outcomes in the cuckoo search algorithm. The experimental results show that the proposed CCSA model enhances accuracy and reduces uncertainty compared to other existing approaches.

关键词： Chaos Cuckoo Search Algorithm computer vision technology Image processing

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