Computer Vision In Sports

The first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life-cycle of a sports event, the text then progresses to examine cutting-edge techniques for tracking the ball, obtaining the whereabouts and pose of the players, and identifying the sport being played from video footage. The work concludes by investigating a selection of systems for the automatic analysis and classification of sports play. The insights provided by this pioneering collection will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.

It seems that artificial intelligence (AI) is always just five years away, but it never arrives. Recently, however. developments have made the practical utility of game theory a genuine reality. Will sport provide the petri dish in which AI will prove itself? What do domain specialists like managers and coaches want to know that they can’t currently find out, and can AI provide the answer? What competitive advantages might AI provide for recruitment, performance and tactics, health and fitness, pedagogy, broadcasting, eSports, gambling and stadium design in the future? Written by leading experts in both sports management and AI, AI for Sports begins to answer these and many other questions on the future of AI for sports.

Computer vision has made enormous progress in recent years, and its applications are multifaceted and growing quickly, while many challenges still remain. This book brings together a range of leading researchers to examine a wide variety of research directions, challenges, and prospects for computer vision and its applications. This book highlights various core challenges as well as solutions by leading researchers in the field. It covers such important topics as data-driven AI, biometrics, digital forensics, healthcare, robotics, entertainment and XR, autonomous driving, sports analytics, and neuromorphic computing, covering both academic and industry R&D perspectives. Providing a mix of breadth and depth, this book will have an impact across the fields of computer vision, imaging, and AI. Computer Vision: Challenges, Trends, and Opportunities covers timely and important aspects of computer vision and its applications, highlighting the challenges ahead and providing a range of perspectives from top researchers around the world. A substantial compilation of ideas and state-of-the-art solutions, it will be of great benefit to students, researchers, and industry practitioners.

"The AI Revolution in Sports" delves into the transformative impact of artificial intelligence on the world of athletics. The book explores how AI is revolutionizing sports analytics, enhancing performance through data-driven insights, and transforming training methodologies. By examining real-world examples, it highlights AI's role in injury prevention, game strategy optimization, and fan engagement. From sophisticated algorithms that predict player performance to virtual reality systems that simulate game scenarios, the book showcases the cutting-edge technologies redefining the sports landscape. It also addresses ethical considerations and the future trajectory of AI in sports, making it an essential read for athletes, coaches, and sports enthusiasts eager to understand the profound changes AI is bringing to their favorite games.

This two-volume set (CCIS 1147, CCIS 1148) constitutes the refereed proceedings of the 4th International Conference on Computer Vision and Image Processing. held in Jaipur, India, in September 2019. The 73 full papers and 10 short papers were carefully reviewed and selected from 202 submissions. The papers are organized by the topical headings in two parts. Part I: Biometrics; Computer Forensic; Computer Vision; Dimension Reduction; Healthcare Information Systems; Image Processing; Image segmentation; Information Retrieval; Instance based learning; Machine Learning.Part II: ​Neural Network; Object Detection; Object Recognition; Online Handwriting Recognition; Optical Character Recognition; Security and Privacy; Unsupervised Clustering.

This book constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.

Computers are a fundamentally important tool in sport science research, sports performance analysis and, increasingly, in coaching and education programmes in sport. This book defines the field of ‘sport informatics’, explaining how computer science can be used to solve sport-related problems, in both research and applied aspects. Beginning with a clear explanation of the functional principles of hardware and software, the book examines the key functional areas in which computer science is employed in sport, including: knowledge discovery and database development data acquisition, including devices for measuring performance data motion tracking and analysis systems modelling and simulation match analysis systems e-learning and multimedia in sports education Bridging the gap between theory and practice, this book is important reading for any student, researcher or practitioner working in sport science, sport performance analysis, research methods in sport, applied computer science or informatics.