Video Analytics in Elite Soccer: A Distributed Computing Perspective

Ubiquitous sensors and Internet of Things (IoT)technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post-game. New methods, including machine learning, image, and video processing, have been developed for performance evaluation, allowing the analyst to track the performance of a player in real-time. Following FIFA’s 2015 approval of electronics performance and tracking system during games, performance data of a single player or the entire team is allowed to be collected using GPS-based wearables. Data from practice sessions outside the sporting arena is being collected in greater numbers than ever before. Realizing the significance of data in professional soccer, this paper presents video analytics, examines recent state-of-the-art literature in elite soccer, and summarizes existing real-time video analytics algorithms. We also discuss real-time crowdsourcing of the obtained data, tactical and technical performance, distributed computing, and its importance in video analytics and propose a future research perspective.acceptedVersio

Bagadus: next generation sport analysis and multimedia platform using camera array and sensor networks

Today, a large number of (elite) sports clubs spend a large amount of resources to analyze their game performance, either manually or using one of the many existing analytics tools. In the area of soccer, there exist several systems where trainers and coaches can analyze the game play in order to improve the performance. However, most of these systems are cumbersome and relies on manual work from many people and/or heavy video processing. In this thesis, we present Bagadus, a prototype of a soccer analysis application which integrates a sensor system, soccer analytics annotations and video processing of a video camera array. The prototype is currently installed at Alfheim Stadium in Norway, and we demonstrate how the system can follow and zoom in on particular player(s), and search for and playout events from the games using the stitched panorama video and/or the camera switching mode

Bagadus - et fotballanalytisk verktøy En implementasjon basert på fysiske spillerdata for automatisk generering av statistikk og videosammendrag

Flere eksisterende systemer for fotballanalyse krever at trenere og andre brukere manuelt må hente og redigere video av kamper. Dette kan medføre et høyt tidsbruk når bestemte kampsituasjoner skal undersøkes og analyseres. I denne oppgaven presenteres et bidrag til en slik problemstilling, der tid og automatisering står helt sentralt. Vi designer og implementerer en prototype av et post-kamp analyseverktøy. Prototypen er installert på Alfheim stadion i Tromsø og integrerer Bagadus eksisterende sensor- og videosystem. Sensorsystemet produserer informasjon om spillernes posisjoner og bevegelser på banen under kampene, og fem kameraer under stadiontaket tar opp video. Prototypen inneholder optimaliserte spørringer mot Bagadus-databasen og returnerer statistikk og tidspunkt i kamper hvor bestemte hendelser oppstår. Tidspunktene brukes deretter til å hente video. Vi viser i denne oppgaven hvordan disse spørringene genererer videosammendrag i løpet av sekunder, et aspekt som muliggjør gjennomføring av hurtig og effektiv kampanalyse

Implementation of a distributed real-time video panorama pipeline for creating high quality virtual views

Today, we are continuously looking for more immersive video systems. Such systems, however, require more content, which can be costly to produce. A full panorama, covering regions of interest, can contain all the information required, but can be difficult to view in its entirety. In this thesis, we discuss a method for creating virtual views from a cylindrical panorama, allowing multiple users to create individual virtual cameras from the same panorama video. We discuss how this method can be used for video delivery, but emphasize on the creation of the initial panorama. The panorama must be created in real-time, and with very high quality. We design and implement a prototype recording pipeline, installed at a soccer stadium, as a part of the Bagadus project. We describe a pipeline capable of producing 4K panorama videos from five HD cameras, in real-time, with possibilities for further upscaling. We explain how the cylindrical panorama can be created, with minimal computational cost and without visible seams. The cameras of our prototype system record video in the incomplete Bayer format, and we also investigate which debayering algorithms are best suited for recording multiple high resolution video streams in real-time

Bagadus App: Notational data capture and instant video analysis using mobile devices

Enormous amounts of money and other resources are poured into professional soccer today. Teams will do anything to get a competitive advantage, including investing heavily in new technology for player development and analysis. In this thesis, we investigate and implement an instant analytical system that captures sports notational data and combines it with high-quality virtual view video from the Bagadus system, removing the manual labor of traditional video analysis. We present a multi-platform mobile application and a playback system, which together act as a state-of-the-art analytical tool providing soccer experts with the means of capturing annotations and immediately play back zoomable and pannable video on stadium big screens, computers and mobile devices. By controlling remote playback and drawing on video through the app, sports professionals can provide instant, video-backed analysis of interesting situations on the pitch to players, analysts or even spectators. We investigate how to best design, implement and combine these components into a Instant Replay Analytical Subsystem for the Bagadus project to create anautomated way of viewing and controlling video based on annotations. We describe how the system is optimized in terms of performance, to achieve real-time video control and drawing; scalability, by minimizing network data and memory usage; and usability, through a user-tested interface optimized for accuracy and speed for notational data capture, as well as user customization based on roles and easy filtering of annotations. The system has been tested and adapted through real life scenarios at Alfheim Stadium for Tromsø Idrettslag (TIL) and at Ullevaal Stadion for the Norway national football team

Bagadus App: Notational data capture and instant video analysis using mobile devices

Enormous amounts of money and other resources are poured into professional soccer today. Teams will do anything to get a competitive advantage, including investing heavily in new technology for player development and analysis. In this thesis, we investigate and implement an instant analytical system that captures sports notational data and combines it with high-quality virtual view video from the Bagadus system, removing the manual labor of traditional video analysis. We present a multi-platform mobile application and a playback system, which together act as a state-of-the-art analytical tool providing soccer experts with the means of capturing annotations and immediately play back zoomable and pannable video on stadium big screens, computers and mobile devices. By controlling remote playback and drawing on video through the app, sports professionals can provide instant, video-backed analysis of interesting situations on the pitch to players, analysts or even spectators. We investigate how to best design, implement and combine these components into a Instant Replay Analytical Subsystem for the Bagadus project to create an automated way of viewing and controlling video based on annotations. We describe how the system is optimized in terms of performance, to achieve real-time video control and drawing; scalability, by minimizing network data and memory usage; and usability, through a user tested interface optimized for accuracy and speed for notational data capture, as well as user customization based on roles and easy filtering of annotations. The system has been tested and adapted through real life scenarios at Alfheim Stadium for Tromsø Idrettslag (TIL) and at Ullevaal Stadion for the Norway national football team

Distributed crowd-based annotation of soccer games using mobile devices

Soccer is one of the most loved sports in the world. Millions of people either follow the sport or are actually involved in its practice. Soccer also moves huge financial amounts every year and therefore teams always thrive to be better than the competition. New technologies have become a common place both in the preparation of the games and on the analysis of the games after they are concluded. In this paper, the authors will present a developed system, based on the usage of distributed mobile devices, that will enable the annotation of soccer matches, either in real time or after the matched is concluded (through the observation of other media). The capture of relevant events in the game can be used to better analyse the game and the performance of individual players fostering improvements and better decisions in the future. The application is implemented in the Android platform so that it can be easily installed by typical soccer fans empowering them as match annotators. This crowd of annotators, although not experts, can collectively provide a robust and rich annotation for soccer matches.info:eu-repo/semantics/publishedVersio

Be your own cameraman: real-time support for zooming and panning into stored and live panoramic video

International audienceHigh-resolution panoramic video with a wide eld-of-view is popular in many contexts. However, in many examples, like surveillance and sports, it is often desirable to zoom and pan into the generated video. A challenge in this respect is real-time support, but in this demo, we present an end-to- end real-time panorama system with interactive zoom and panning. Our system installed at Alfheim stadium, a Nor- wegian premier league soccer team, generates a cylindrical panorama from ve 2K cameras live where the perspective is corrected in real-time when presented to the client. This gives a better and more natural zoom compared to existing systems using perspective panoramas and zoom operations using plain crop. Our experimental results indicate that vir- tual views can be generated far below the frame-rate thresh- old, i.e., on a GPU, the processing requirement per frame is about 10 milliseconds. The proposed demo lets participants interactively zoom and pan into stored panorama videos generated at Alfheim stadium and from a live 2-camera array on-site

Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance

One in twenty-five patients admitted to a hospital will suffer from a hospital acquired infection. If we can intelligently track healthcare staff, patients, and visitors, we can better understand the sources of such infections. We envision a smart hospital capable of increasing operational efficiency and improving patient care with less spending. In this paper, we propose a non-intrusive vision-based system for tracking people's activity in hospitals. We evaluate our method for the problem of measuring hand hygiene compliance. Empirically, our method outperforms existing solutions such as proximity-based techniques and covert in-person observational studies. We present intuitive, qualitative results that analyze human movement patterns and conduct spatial analytics which convey our method's interpretability. This work is a step towards a computer-vision based smart hospital and demonstrates promising results for reducing hospital acquired infections.Comment: Machine Learning for Healthcare Conference (MLHC