With the development of civil engineering sustainability, the scope of corresponding research covers a broader range. It is difficult for researchers to master the holistic situation of the study, leading to duplication and lag of their research. Therefore, this paper aims to present a state-of-the-art of the research of civil engineering sustainability by adopting two new methods (bibliometric and social network analysis) to review the literature of this field. It is concluded that the existing research takes engineering as the main subject to improve its sustainability through technologies. Current research mainly focuses on technological innovations and evaluations of environmental impacts in the fields of construction technology, energy consumption, material preparation, and design. The countries with the largest number of published articles are the United States and China. The Hong Kong Polytechnic University is the institution that has published more articles than others. Journal of Cleaner Production and Sustainability are the journals that have published the most articles. For the researchers, a professor of the University of Adelaide is the researcher who has published the most articles, and experts from South China University of Technology, Chongqing University, and University of Brighton are the main hubs among different researchers.
In order to better grasp the research progress of physical training, explore the current research hotspots and trends, and provide a theoretical basis for subsequent research. The current physical fitness training was systematically analyzed through visual analysis software CiteSpace 6.1.R6 and VOSviewer 1.6.18 by confirming the subject search term TS = ("physical fitness training" or "physical training"). After data cleaning. The result was 733 relevant papers. The results showed that the overall trend of physical training was stable over the past 10 years. The visual graph analysis revealed that Orr, R.M. was the author with the highest volume of articles, reaching 12 authors Kraemer. W.J. was the one with the highest volume of articles per article reaching 19.5 times/article, and the connection between author groups needs to be further strengthened; the University of São Paulo institution had the highest number of articles, reaching 31, and from a regional perspective, the United States was in the lead; keyword clustering could be a total of classify 8 clusters, in which high-frequency keywords appear in the order of sports, performance, intensity, physical fitness, sports injuries, education, and women. The focus on women's issues is also increasing. From the epidemic vocabulary and time presentation graph, physical training is more prominent in the medical field, with keywords sports injury, epidemic, health, and physical training as the main keywords, and people in the post-epidemic era emphasize more on healthy lifestyles. The visualization analysis shows in detail the current research hotspots and development trends of physical fitness training, which show diversified development trends in the process of continuous expansion.
Based on computer vision technology, this paper presents a human motion analysis and target tracking technology based on computer vision. In terms of moving target detection, the current moving target detection technology is summarized, and some experimental results of the algorithm are given. The background difference method under monocular camera is emphatically analyzed. The preliminary human contour is obtained by the background difference method. In order to obtain a smoother target contour, the mathematical morphology is used to remove the noise, and the judgment algorithm of the size of the image connected domain is added. A specific threshold is set to remove the connected domain of the noise block less than the threshold. In the aspect of human motion recognition, this paper selects human motion features, including minimum external rectangle aspect ratio, rectangularity, circularity, and moment invariant. The criteria for selecting human motion features are strong noise resistance and obvious distinction. Then, the three types of human motion images are classified and recognized. After cross-validation and parameter optimization, the recognition accuracy is significantly improved. The experimental results show that the video sequence collected in the field has a total of 376 frames, and the frame rate is 10 frames/s. Due to the small traffic, the mean shift algorithm based on adaptive feature fusion is used to track the target every 2-3 frames. And set the inverse X direction as the direction of entering the scene and the X direction as the direction of moving out of the scene so that the allowable error of the distance between the detection and tracking results is 10. The weight of each feature is dynamically updated by the similarity between the candidate model and the target model, which solves the problem that the mean shift algorithm is not robust enough when similar objects are occluded and interfered and achieves more accurate tracking.
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