Artificial Intelligence and Big Data Forum最新文献

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Optimization of the initial position selection based on the Coverage Path Planning (CPP) algorithm 基于覆盖路径规划(CPP)算法的初始位置选择优化
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2672143
Chenghao Li
{"title":"Optimization of the initial position selection based on the Coverage Path Planning (CPP) algorithm","authors":"Chenghao Li","doi":"10.1117/12.2672143","DOIUrl":"https://doi.org/10.1117/12.2672143","url":null,"abstract":"The task of Coverage Path Planning (CPP) is to generate a route that satisfies the condition of reaching every possible area of a specific room. The room is divided into grids whose sizes are the same as the target moving in the space. Basically, CPP algorithms are classified into classical algorithms and heuristic-based algorithms. This paper focuses on one of the heuristic-based algorithms, A*, and applies four heuristic mapping functions to generate the coverage path. Subsequently, every grid is considered as the initial point where the path is generated, and the resulting steps and the cost of the total steps are compared. Besides searching for the routes available to cover the whole map, the ultimate target of the algorithm under discussion is to select the best initial point among all of the grids. This step ensures that the valid path generated by the algorithm is the shortest or the most commercial result.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129291997","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
Dance somersault gesture recognition based on multi-scale depth feature fusion 基于多尺度深度特征融合的舞蹈空翻手势识别
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671568
Lusi Huang
{"title":"Dance somersault gesture recognition based on multi-scale depth feature fusion","authors":"Lusi Huang","doi":"10.1117/12.2671568","DOIUrl":"https://doi.org/10.1117/12.2671568","url":null,"abstract":"In order to explore the problem of dance somersault gesture recognition, a kind of dance somersault gesture recognition based on multi-scale depth feature fusion is proposed. Methods Through the information recommendation of key technical problems and solutions based on multi-scale depth feature fusion, the research of dance somersault gesture recognition was explored. The research shows that the efficiency of dance somersault gesture recognition based on multi-scale depth feature fusion is about 4.6% higher than that of traditional methods. The acquisition of main video information has always been inclined to obtain video key frames. However, in the face of videos with strong continuity and low repetition between human posture sequences in various movements, only key frames can't represent all the effective information of the videos. Most algorithms excessively pursue the differences between action categories, thus ignoring the degree of \"cohesion\" between simple actions within actions.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123984088","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
Research on digital sculpture design based on virtual reality technology 基于虚拟现实技术的数字雕塑设计研究
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671830
Kun Zhang
{"title":"Research on digital sculpture design based on virtual reality technology","authors":"Kun Zhang","doi":"10.1117/12.2671830","DOIUrl":"https://doi.org/10.1117/12.2671830","url":null,"abstract":"Sculpture design and creation is a highly complex art form, requiring designers to have high artistic quality, innovation and practical ability. Traditional sculpture design can meet the needs of people for sculpture design and use at a certain stage, but it requires more links from the initial conception of the designer to the final presentation of the work. The efficiency of sculpture design is greatly limited, and the production process of the work consumes more materials. For this reason, this paper establishes a digital sculpture design method based on VR technology. By analyzing the application basis of VR technology in digital sculpture design, a sculpture design model construction method based on eye-movement data collection and feature extraction is established. Secondly, the feasibility of VR technology application is further verified by analyzing the application advantages of VR technology application compared with traditional sculpture design. In addition, this paper establishes a VR-based digital sculpture design and construction process, and analyses the beneficial effects of VR technology on sculpture design. The research in this paper verifies the effectiveness and feasibility of VR sculpture design, which contributes to the diversified development of sculpture design.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123206147","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
A 3D hand pose estimation architecture based on depth camera 一种基于深度相机的三维手部姿态估计体系结构
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671350
Zhaolong Deng, Yanliang Qiu, Xintao Xie, Zuanhui Lin
{"title":"A 3D hand pose estimation architecture based on depth camera","authors":"Zhaolong Deng, Yanliang Qiu, Xintao Xie, Zuanhui Lin","doi":"10.1117/12.2671350","DOIUrl":"https://doi.org/10.1117/12.2671350","url":null,"abstract":"Considering the problem of the inability to obtain accurate depth information in 3D pose estimation, this research attempts to use a depth camera to obtain accurate depth information to solve this problem and achieve good results. In the process of research, it is found that the general object detection and evaluation method is not accurate enough under the framework proposed in this paper, so this research proposes an evaluation method suitable for this framework. A standardizer is also designed to optimize the detection effect while achieving efficient tracking objects. Ultimately, inference time is reduced by 35%. The implementation of this research architecture is open-sourced at https://github.com/DumbZarro/BuddHand.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125408117","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
The research of lightweight method for the electric and electronic systems’ BIM model 电气电子系统BIM模型的轻量化方法研究
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671236
J. Huo, Guanxiang Pei, Tingjuan Wang, Jinquan Liu
{"title":"The research of lightweight method for the electric and electronic systems’ BIM model","authors":"J. Huo, Guanxiang Pei, Tingjuan Wang, Jinquan Liu","doi":"10.1117/12.2671236","DOIUrl":"https://doi.org/10.1117/12.2671236","url":null,"abstract":"In view of the problems of BIM model, low data transmission efficiency, cumbersome data conversion and poor BIM rendering, An optimized and improved method is proposed to realize the lightweight of electric &electronic systems’ BIM model. This method uses RevitAPI to generate a custom GLTF model, split and preprocess the overall model, use the optimized model simplification method to ensure the details of the model, generate the custom GLTF data format, complete the lightweight of BIM model. Taking the model in the electric &electronic systems’ project as an example, a high-speed railway station and components were selected for this experiment to verify and compare the proposed method. The results show that the lightweight method of BIM model effectively reduces the model data quantity, improves the real-time rendering efficiency and optimizes the loading effect.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122040065","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
Research on crack identification method of concrete structure based on digital image information analysis 基于数字图像信息分析的混凝土结构裂缝识别方法研究
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671444
Cao Wang, Tao Yang, Guodong Li, H. Yang, Fengting Li, Dapeng Liu
{"title":"Research on crack identification method of concrete structure based on digital image information analysis","authors":"Cao Wang, Tao Yang, Guodong Li, H. Yang, Fengting Li, Dapeng Liu","doi":"10.1117/12.2671444","DOIUrl":"https://doi.org/10.1117/12.2671444","url":null,"abstract":"Most of the subway stations are below the groundwater level, so it is particularly important to do a good job in waterproofing. For the leakage disease of subway station structure, detection is the method and identification is the purpose. There are many types of urban subway station structural leakage diseases, and it is not easy to identify the diseases in all directions. Based on the summary and analysis of the common identification methods of seepage water diseases in subway stations, the crack digital images obtained in a non-contact way are taken as the research objects. Starting from the crack characteristics and the principle of digital image processing algorithm, the traditional algorithm is improved and optimized to obtain a detection algorithm more suitable for the digital image of concrete structural cracks, which is applied to the identification of structural cracks in subway stations. Compared with other manual methods, this method is more accurate and can save a lot of time and cost.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126576103","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
Research on on-line monitoring system for operation environment of converter station valve hall and sensor distribution method 换流站阀厅运行环境在线监测系统及传感器分布方法的研究
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671915
Yanwei Wu, Yi Gao, Yingcheng Liu, Yang Zhao, Zijun He, Miaoyi Li
{"title":"Research on on-line monitoring system for operation environment of converter station valve hall and sensor distribution method","authors":"Yanwei Wu, Yi Gao, Yingcheng Liu, Yang Zhao, Zijun He, Miaoyi Li","doi":"10.1117/12.2671915","DOIUrl":"https://doi.org/10.1117/12.2671915","url":null,"abstract":"In the valve hall of converter station, the operating environment has very strict requirements for the valve hall. Due to the space, equipment and other factors of the valve hall of converter station, it is very difficult for traditional monitoring methods to achieve the operating environment of the valve hall of converter station. In order to achieve online real-time monitoring, this paper adopts the method of multi-sensor distribution to achieve, simulates the converter station valve hall through modeling, and conducts reasonable sensor distribution to achieve all-round real-time monitoring of the valve hall, including temperature and humidity, electromagnetic strength, particles, etc. Through real-time monitoring, the measures can be pretreated to avoid accidents.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117221261","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
Road extraction from high-resolution remote sensing images based on the combination of K-means and SVM 基于K-means与SVM结合的高分辨率遥感影像道路提取
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671264
Yanmei Wang, Wei Jiang, Pengfei Feng
{"title":"Road extraction from high-resolution remote sensing images based on the combination of K-means and SVM","authors":"Yanmei Wang, Wei Jiang, Pengfei Feng","doi":"10.1117/12.2671264","DOIUrl":"https://doi.org/10.1117/12.2671264","url":null,"abstract":"Extracting road information from high-resolution remote sensing images is an important way to obtain basic data of geographic information. In this paper, firstly, the shortcomings of K-means and SVM are analyzed, and then the road information is extracted by the algorithm combining K-means and SVM. The experimental results show that the combined algorithm has higher accuracy and lower missing error than the single algorithm. The experimental results can provide some technical support for future road information extraction.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129002508","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
An adaptive coverage path planning method considering energy constraints 考虑能量约束的自适应覆盖路径规划方法
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2672136
S. Shao
{"title":"An adaptive coverage path planning method considering energy constraints","authors":"S. Shao","doi":"10.1117/12.2672136","DOIUrl":"https://doi.org/10.1117/12.2672136","url":null,"abstract":"Coverage path planning algorithms are widely used by many robots conducting work like floor sweeping, map generating and underwater searching. One of the practical methods is the Backtracking Spiral Algorithm (BSA), which is efficient and complete coverage guaranteed. In practice, however, autonomous robots are faced with the problem of energy constraints. The duration of the battery of a robot is usually limited. This paper presents an adaptive coverage path planning method based on BSA considering the energy constraints. The objective of this method is to minimise the total length of the path the robot travelled to recharge while guaranteeing complete coverage. This method uses an estimation strategy which would use the energy consumption of the last round as a conjecture of that of the next round and recharge when the remaining energy would probably be insufficient to complete the next round while the robot passes nearby the recharging station. A simulation result is then provided to serve as proof of this method.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131615564","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 online learning evaluation based on 2D and 3D image processing technology 基于二维和三维图像处理技术的在线学习评价研究
Artificial Intelligence and Big Data Forum Pub Date : 2023-03-16 DOI: 10.1117/12.2671835
Tongyao Ju, Xiangping Shen, Jun Yu
{"title":"Study on the online learning evaluation based on 2D and 3D image processing technology","authors":"Tongyao Ju, Xiangping Shen, Jun Yu","doi":"10.1117/12.2671835","DOIUrl":"https://doi.org/10.1117/12.2671835","url":null,"abstract":"In recent years, the outbreak of the COVID-19 epidemic has posed a serious threat to the life safety of people around the world, which has also led to the development of a series of online learning assessment technologies. Through the research and development of a variety of online learning platforms such as WeChat, Tencent Classroom and Netease Cloud Classroom, schools can carry out online learning assessment, which also promotes the rapid development of online learning technology. Through 2D and 3D recognition technology, the online learning platform can recognize face and pose changes. Based on 2D and 3D image processing technology, we can evaluate students' online learning, which will identify students' learning state and emotion. Through the granulation of teaching evaluation, online learning platform can accurately evaluate and analyze the teaching process, which can realize real-time teaching evaluation of students' learning status, including no one, many people, distraction and fatigue. Through relevant algorithms, the online learning platform can realize the assessment of students' head posture, which will give real-time warning of learning fatigue. Firstly, this paper analyzes the framework of online learning quality assessment. Then, this paper analyzes the face recognition and head pose recognition technology. Finally, some suggestions are put forward.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130769322","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
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