Sports Image Research Articles

Update on sports imaging

Sports Imaging has dramatically increased in the past decade with increasing number of adolescents, young and middle-aged adults participating in non-competitive/hobby sports. Therefore, sports injuries are no longer confined to elite athletes. Furthermore, newer forms of sports such as mountain climbing, pickle ball and curling etc. are gaining popularity. Majority of the injuries in sports medicine are from musculoskeletal trauma. Therefore, it is imperative that the musculoskeletal radiologist becomes familiar with various sports related injury patterns as these are commonly encountered in daily practice. This update aims to briefly encapsulate the major aspects of sports imaging. It includes the imaging manifestations of various types of musculoskeletal injuries on different modalities (commonly US and MRI) and briefly mentions the various image guided interventions, performed both on the sports field and in the hospital setting.

Development significance and structure analysis of sports video image analysis system based on VR

Modern science and technology is highly differentiated and concentrated, and has also entered a new stage of multidisciplinary comprehensive utilization. Especially, VR technology has played a great role in competitive sports training. Intelligent video analysis system is a key point of modern video development. With the development of computer technology and the gradual progress of video technology, intelligent video analysis system has broad development space. In this paper, a key algorithm SISA (Sports Image Segmentation Algorithm) is designed. The algorithm improves and optimizes the semantic segmentation algorithm by using hole convolution, pyramid pooling and trainable conditional random field structure, and uses key node detection algorithm to enhance the segmentation effect of small objects. The common methods to realize virtual human animation are manual marking, motion capture and automatic recognition. In order to reduce the workload of manual marking, avoid the high cost of motion capture and make up for the precision error of automatic recognition, it can be practically applied to the guidance of physical training.

Framework design of sports image analysis system based on three-dimensional image technology

Sports image analysis system based on computer vision image processing technology is a hot project in urgent need of society at present. Due to various objective and subjective factors, the application environment of intelligent module in sports image analysis system is limited, and there is still a certain gap from the social requirements. In this paper, the hardware selection of the system is focused on the applicability and cost. Based on the idea of the inherent hardware of the organizers of the grass-roots sports meeting, the system combining camera, video capture card and PC is selected, which has a high ratio of information to price. A fuzzy enhancement system of 3D digital image based on data mining is designed. Analyze the motion information in video stream to a certain extent, extract the physical characteristics and behavioral characteristics of moving objects, and use the fusion of the two to complete the dynamic target analysis in video surveillance images. The sports image analysis system based on 3D image technology designed in this paper has good universality and good application and popularization value.

The Correct Use of Images with Child Protection in Sport

The aim of this research is to produce a study that will guide sports clubs and organizations to use photos and videos without harming and abuse children and to prepare regulations for the correct usage of images in child sports. In this study, document analysis technique from the qualitative research methods was used. For this purpose, the relevant regulations and practices of major national and international sports organizations which has implementation about child safeguarding in sports were examined in terms of general situation, basic principles, risks and measures in the usage of photography and video. Regulations on correct usage of photography and video of 16 different sports organizations from England, Ireland, the United States of America, Australia and New Zealand were included. The obtained data were analyzed using descriptive analysis method. The findings show that in the use of photography and video policies implemented by national and international sports organizations, precautions are taken to ensure that permission is sought from parents to use children's images, that personal information of children is not included in image sharing, and that inappropriate angles in photographs and video shoots are avoided. Finally, these policies ban the recording of images in locker rooms, health rooms etc. and it is forbidden to enter these areas with phones etc. that can record images.

Sports Recognition using Convolutional Neural Network with Optimization Techniques from Images and Live Streams

This paper deals with the issue of automated image and video recognition of sports. It is a category of appreciation of human behavior, which is a very difficult task in the present day to classify images and video clips into a categorized gallery. This research paper proposes a sports detection system using a deeper CNN model that combines a fully connected layer with fine-tuning. It is applied to classify five individual sports groups through images and videos. In this work, we use a video classification method based on the image. Extended Resnet50 and VGG16 two pre-trained Deep CNNs are applied to build this sports detection system. RMSProp, ADAM & SGD optimizers are used to train the extended CNN models for five Epochs on the proposed 5sports dataset by handpicking thousands of sports images from the internet to very smoothly classify the five different types of sports. Training accuracy of approximately 83% is observed for ResNet50 with an SGD optimizer for 5 sports classes and 95% is observed for 3 sports classes.

Moving Target Localization in Sports Image Sequence Based on Optimized Particle Filter Hybrid Tracking Algorithm

This paper proposes a fusion stadium positioning algorithm, which uses self-optimizing particle filter to integrate the improved athlete dead reckoning and WiFi position fingerprint algorithm for stadium positioning. In order to determine the initial absolute position of the stadium positioning, for athletes entering the stadium from the outside, a seamless switching algorithm outside the stadium is proposed, using the characteristics of high-altitude satellite GPS to find a suitable switching point as the initial absolute position. If in the stadium, WiFi static positioning determines the initial absolute position. Then, aiming at the problem that the poorly diversified particles cannot be better integrated and localized, a self-optimized particle filter algorithm is proposed. After resampling and retaining high-weight particles, the characteristics of low-weight particles are embedded in the copied high-weight particles. This can improve diversity, and we finally carry out fusion positioning. The target tracking algorithm based on Mean Shift has a fixed-scale tracking window, and the tracking effect of variable-size targets is not ideal. In this paper, an affine transformation algorithm is introduced to improve it. First, we iterate the adjacent image frames in reverse Mean Shift to determine the center position of the target and then use the corner matching method to perform template matching on the target to adjust the size of the tracking window. Through simulation verification, it is proved that the optimized particle filter hybrid tracking algorithm can achieve the ideal result when the target size changes. For the image sequence S1, the tracking window of the 20th frame and the 40th frame has a small offset, but the optimal position can be quickly found by Mean Shift iteration. For the image sequence S2, between the 40th frame and the 60th frame, the target occlusion causes the accuracy of the target template to decrease, and the Bhattacharyya coefficient is at a relatively low value. For the image sequence S3, the tracking effect of the optimized particle filter hybrid tracking algorithm meets the requirements.

RETRACTED ARTICLE: Coastal land use planning and beach sports image recognition based on high-resolution remote sensing images

RETRACTED ARTICLE: Coastal land use planning and beach sports image recognition based on high-resolution remote sensing images

Controlling messy errors in virtual reconstruction of random sports image capture points for complex systems

When athletes perform different sports, the angles of joints and the speed of movement are different, which causes the feature capture points to not correspond to the key areas well. This results in forming feature messy correspondence errors, and affecting the accuracy of shape basis calculation. The traditional 3D reconstruction algorithms for sports images are affected by the messy profile, and it is difficult to counter the accuracy of later modeling. Therefore, an error control mechanism in the virtual modernization of random sports image collected points is recommended for the complex systems. In this work, the factorization method is used to establish a 3-D dynamic simulation structure of the human body when it is moving. The stolt transformation is implemented for adjusting the azimuth offset rate of all image capturing regions, such that it cannot generate excessive errors during feature matching. The large messy residual error is used for third-order signal compensation for realizing the 3-D dynamic simulation structure in the humanoid signal image sequence. The observed outcomes shows that this approach improves the authenticity of 3-D dynamic simulation of human signal image classifications. Using 150 images and 915 key points, an authenticity coefficient of 0.86 is achieved by the proposed approach outperforming the other state-of-the-art algorithms.

The Sporting Bubble as Gilded Cage

The Sporting Bubble as Gilded Cage

Formation of sports image by mass communication media

Formation of sports image by mass communication media

THE RELATIONSHIP BETWEEN SPORTS FACILITY SERVICE QUALITY AND CUSTOMER SATISFACTION OF GOR SAPARUA

Public service is a government obligation in fulfilling the rights of every citizen. To facilitate the delivery of government services to the community, a public service model is needed. One of them in public service is sports. Of course, sports play an important role in the development of human life. Public sports facilities have played a very important role in promoting physical activity and participation in recreational sports activities. Therefore, there are significant efforts to continuously improve the image of recreational sports and to pursue the improvement of the service quality of public sports facilities. Several dimensions can be measured to determine service quality on customer satisfaction, including tangibility, reliability, assurance, responsiveness, and empathy. This study aims to determine whether there is a relationship between service quality and customer satisfaction who visits Saparua Sports Hall, Bandung City. This type of research is correlational and the method used is quantitative with an accidental sampling technique with a sample size of 100 respondents. The overall result of the study is that there is a relationship between service quality and customer satisfaction who visits Saparua Sports Hall.

Exploration of Visual Image Design in Sports Universities—Taking the Visual Image Design of Wuhan Institute of Physical Education as an Example

The university visual identification system is an extension of the enterprise visual image identification system, which displays the university visual brand image jointly through the logo, standard color, standard font, auxiliary graphics and standard combination. As far as the visual image recognition system of sports colleges and universities is concerned, the refinement, digitization and standardization of the image are important means to realize the visual symbol of sports characteristics and its attached value and cultural connotation. This article from the perspective of visual communication design, following the integration and fine-tuning and complement, using the theory of the method of literature study method, graphic method and contrast method, etc, has carried on the induction summary to the visual image of sports colleges and universities at home and abroad, taking Wuhan sports college as an example, discusses the basic connotation of Visual identification system, Wuhan institute of physical education including signs, standard colors, fonts, graphics and standards, etc., and the design result is given.

Job Versus Hercules: Virtue in the Articles of the Byzantine Suda Dictionary of the 10th Century

Introduction. In ancient mythology, the image of Hercules is one of the most popular, and his heroic cult is one of the most common. Having emerged from the “conglomerate of folk tales”, the image of Hercules was actively assimilated by the Greek and then Roman literary tradition. Hercules was a very popular hero among Greek tragic and especially comic poets. In Roman times, the final systematization of the image took place. The key role in this process was played by the works of Apollodorus “The Mythological Library” (2nd century BC), “Pictures” by Philostratus the Younger (2nd century BC) and “Description of Hellas” by Pausanias (2nd century BC). Within the framework of the classical tradition, the image of Hercules in Roman times was finally formed and unambiguous. Hercules is a hero, a demigod, the son of Zeus and Alcmene, who possessed amazing strength, who killed his children (and the children of his brother Iphicles) in an act of madness. He performed 12 labours at the request of Eurystheus. Hercules lived with the Lydian queen Omphale dressing in a woman’s dress. He was poisoned by his wife Deianira, burned at the stake on Mount Eta and ascended to Olympus, where he became the spouse of Hebe. Methods. The hermeneutic methodology, which ensured the correct understanding and interpretation of the text of the Suda dictionary and the ancient texts, on which this “antique” dictionary was based, is used in the article. The toolkit of the hermeneutic circle (pre-understanding and understanding of the text, interpretation of the whole based on knowledge of its parts) made it possible to highlight key elements (plots, signs and symbols) of the philosophical image of Hercules in the entries of the dictionary. Results. We can see a kind of “muscular Christianity”, when the strength of the body still corresponds to moral perfection and the withdrawal from the world does not contradict the active entry into the still polis institutions of urban life in Byzantine cities, among which the most important was the hippodrome and sports competitions. Christian authors actively used traditional sports metaphors and images of wrestling, but filled them with new Christian content. In the dictionary of the Suda, there is a kind of replacement of images that embody the samples of virtue. Hercules always loses to Job. It is indicative that the Christian rhetoric, relying on the philosophical symbolism of the apotheosis of Hercules, using the “sports” terminology of struggle, ignores the developed philosophical symbolism of Hercules, and fights against the mythological “fables” about Hercules. Using cynical and stoic terminology, Christian rhetoric opposes the comedic and dramatic image of Hercules, as Herodore of Heracles did in the 5th century BC. That is, the enemy is borrowed from Christian rhetoric along with philosophical symbols and terminology describing a difficult life full of trials as a virtue.

Olympic Games Event Recognition via Transfer Learning with Photobombing Guided Data Augmentation.

Automatic event recognition in sports photos is both an interesting and valuable research topic in the field of computer vision and deep learning. With the rapid increase and the explosive spread of data, which is being captured momentarily, the need for fast and precise access to the right information has become a challenging task with considerable importance for multiple practical applications, i.e., sports image and video search, sport data analysis, healthcare monitoring applications, monitoring and surveillance systems for indoor and outdoor activities, and video captioning. In this paper, we evaluate different deep learning models in recognizing and interpreting the sport events in the Olympic Games. To this end, we collect a dataset dubbed Olympic Games Event Image Dataset (OGED) including 10 different sport events scheduled for the Olympic Games Tokyo 2020. Then, the transfer learning is applied on three popular deep convolutional neural network architectures, namely, AlexNet, VGG-16 and ResNet-50 along with various data augmentation methods. Extensive experiments show that ResNet-50 with the proposed photobombing guided data augmentation achieves 90% in terms of accuracy.

RETRACTED: Target recognition of basketball sports image based on embedded system and internet of things

Current game conflicts and live footage and video recordings in general, and innovations carry the game's financial cycle image recognition with the help of competitors to find data. In any case, the current situation shows that are still young with innovations recognizing the game image. That's why the uses of this study are to disassemble sports images and identify discoveries as an object for application game images. Cameras, video cameras, sensors Advances Infrared is different, For example, using an innovative visual data capture gadget, it has become the basic query for retrieving visual data, but now, in the age of data explosion, how much display it bears is a slightly larger study to capture the benefits. This is one of the most important issues with computer graphics. The basics and the most important task in film production and assignment is that the survey of images can be done as a result of large screen cracks. This article proposes a ball pollution technology computer game that depends on the screen split calculation coordinates.

Application of Convolution Network Model Based on Deep Learning in Sports Image Information Detection

In recent years, convolution neural network has achieved great success in single image super-resolution detection. Compared with the traditional method, this method achieves better reconstruction detection effect. However, the network structure of the existing reconstruction model is shallow, and the convolution kernel has a small acceptance, so it is difficult to learn a wide range of motion image features, which affects the quality of motion image information detection. Aiming at the problems and shortcomings of the existing sports image information detection based on convolution neural network, this paper proposes the application of convolution network model based on deep learning in sports image information detection. In this paper, we get the average SSIM value from the data of set5, set14, bsd100 and urban100 by using the X4 model of different algorithms. The average SSIM value of set5 is 0.865, which shows that the quality of sports image reconstruction and the reconstruction efficiency of the model can be improved by using the local image features of different scales, which provides technical support for sports image information detection. The research in this paper has important practical significance for the further development of the two and the reform of the convolution network model in sports image information detection.

A Hybrid Approach for Semantic Image Annotation

In this study, a framework that generates natural language descriptions of images within a controlled environment is proposed. Previous work on neural networks mostly focused on choosing the right labels and/or increasing the number of related labels to depict an image. However, creating a textual description of an image is a completely different phenomenon, structurally, syntactically, and semantically. The proposed semantic image annotation framework presents a novel combination of deep learning models and aligned annotation results derived from the instances of the ontology classes to generate sentential descriptions of images. Our hybrid approach benefits from the unique combination of deep learning and semantic web technologies. We detect objects from unlabeled sports images using a deep learning model based on a residual network and a feature pyramid network, with the focal loss technique to obtain predictions with high probability. The proposed framework not only produces probabilistically labeled images, but also the contextual results obtained from a knowledge base exploiting the relationship between the objects. The framework’s object detection and prediction performances are tested with two datasets where the first one includes individual instances of images containing everyday scenes of common objects and the second custom dataset contains sports images collected from the web. Moreover, a sample image set is created to obtain annotation result data by applying all framework layers. Experimental results show that the framework is effective in this controlled environment and can be used with other applications via web services within the supported sports domain.

Differences in the Image of Sports due to Extracurricular Sports Experiences in High School: From Two Surveys Targeting University Freshmen

Differences in the Image of Sports due to Extracurricular Sports Experiences in High School: From Two Surveys Targeting University Freshmen

Impact of European Union programs on the activities of the Third Polish Republic’s Parliament in the field of sport in the years 2004-2007

The aim of this paper is to show the impact of European Union programs on the activities of the Third Polish Republic’s Parliament in the field of sport in the years 2004-2007. The Republic of Poland joined the European Union (EU) on 1 May 2004. Since then, it has been co-creating the image of sport in Europe. All activities undertaken by the Polish Parliament in the development of sport after this event were related to programs in the European Union. During the period covered in this paper, the institutions involved in sport in the European Union included the Council of the European Union, the European Parliament, the European Commission and the European Court of Justice. One year after Poland’s accession to the European Union, elections were held for the fifth term of the Polish Sejm (2005-2007). The representatives of the Polish Parliament, during meetings of the Physical Culture and Sport Committee, repeatedly pointed to the possibility of adapting EU programs and their use in the development of sport in Poland. The material presented by the Ministry of Sport and the Office of the European Integration Committee in Warsaw informed about the following programs (mainly investment ones): Sport in the structures of the European Union and European Union Programs for the development of sport, implemented between 2004 and 2006. The most important issues raised by the Committee were those contained in the two most important documents: White Paper on Sport and Independent European Sport Review. As a result of the work of the Parliament of the Republic of Poland during the fifth term of office (2005-2007) in cooperation with the Ministry of Sport and the Parliamentary Physical Culture and Sport Committee, a plan for co-financing projects for the construction, extension or modernization of sports infrastructure under the EU structural programs and the INTERREG III A and EQUAL Community Initiatives was developed. The effect of Poland’s membership in the EU in that period was a gradual elimination of infrastructural negligence and undertaking activities related to the activation of local communities in the area of education and sport. Poland’s membership in the EU so far has brought positive results: increased accessibility of sport thanks to the development of regional infrastructure co-financed by the EU funds and the enrichment of the program offer by supporting projects related to the organization of extracurricular sports activities for children and young people. The positive effects of membership in the field of sport are still being perceived by selected groups and society as a whole.

RETRACTED: Research on segmentation of sports images based on GMMLS method

The transmission is a major economic game broadcast, not just playing games, video files, and can be tracked by image segmentation. However, from the current situation, it can see the video segmentation technology is still immature. Image segmentation is a technique that divides the original image into several different categories. Many of the possible solutions, it can be made available for image segmentation into different motion image segmentation qualities and each, some of the categories. The first step in the preprocessing is to remove the noise from the image. The second level is designed to be based on the proposed Gaussian Mixed Model Level Set (GMMLS), which uses multi-level threshold technology for image segmentation. The GMMLS is expected to realize an image processing method because it is substantially parallel to and consistent with the regional image division processing. And the third process, feature extraction, completion and final motion image classification. Experiments have demonstrated the feasibility of artificial life methods in both luminance and color images. Experimental results show that the algorithm provides fast segmentation with high perceptual segmentation quality while moving the image split view.