A survey of video based action recognition in sports

Sport performance analysis which is crucial in sport practice is used to improve the performance of athletes during the games. Many studies and investigation have been done in detecting different movements of player for notational analysis using either sensor based or video based modality. Recently, vision based modality has become the research interest due to the vast development of video transmission online. There are tremendous experimental studies have been done using vision based modality in sport but only a few review study has been done previously. Hence, we provide a review study on the video based technique to recognize sport action toward establishing the automated notational analysis system. The paper will be organized into four parts. Firstly, we provide an overview of the current existing technologies of the video based sports intelligence systems. Secondly, we review the framework of action recognition in all fields before we further discuss the implementation of deep learning in vision based modality for sport actions. Finally, the paper summarizes the further trend and research direction in action recognition for sports using video approach. We believed that this review study would be very beneficial in providing a complete overview on video based action recognition in sports

Soccer line mark segmentation and classification with stochastic watershed transform

Augmented reality applications are beginning to change the way sports are broadcast, providing richer experiences and valuable insights to fans. The first step of augmented reality systems is camera calibration, possibly based on detecting the line markings of the playing field. Most existing proposals for line detection rely on edge detection and Hough transform, but radial distortion and extraneous edges cause inaccurate or spurious detections of line markings. We propose a novel strategy to automatically and accurately segment and classify line markings. First, line points are segmented thanks to a stochastic watershed transform that is robust to radial distortions, since it makes no assumptions about line straightness, and is unaffected by the presence of players or the ball. The line points are then linked to primitive structures (straight lines and ellipses) thanks to a very efficient procedure that makes no assumptions about the number of primitives that appear in each image. The strategy has been tested on a new and public database composed by 60 annotated images from matches in five stadiums. The results obtained have proven that the proposed strategy is more robust and accurate than existing approaches, achieving successful line mark detection even in challenging conditions.Comment: 18 pages, 11 figure

Automatic field tracking in recorded football games

Trabajo de Fin de Grado en Ingeniería Informática, Facultad de Informática UCM, Departamento de Sistemas Informáticos y Computación, Curso 2021/2022.Este trabajo se ha centrado en el tratamiento para la detección de las líneas correspondientes al terreno de juego de un partido de fútbol a partir de las retransmisiones producidas para la televisión. Una vez aplicados todos los tratamientos previos se procede a la implementación del algoritmo encargado de la detección de las líneas correspondientes al terreno de juego, así como de su identificación y refinamiento buscando la máxima precisión posible y desestimando posibles falsos positivos o líneas irrelevantes para la detección del terreno de juego. Por último, se documenta una breve implementación para un caso de uso concreto a partir de la eliminación del efecto de la perspectiva en la imagen, logrando una imagen resultado en un plano de dos dimensiones, a partir de la cual se abre un extenso campo de investigación y utilidad para diferentes áreas del mundo del fútbol como son los clubes, periodistas, analistas, etc...This work has focused on the processing for detection the lines corresponding to the field of play of a football match from the broadcasts produced for television. Once all the previous treatments have been applied to the image, the algorithm in charge of detecting the lines corresponding to the playing field is implemented, as well as its identification and refinement, seeking the highest possible accuracy and discarding possible false positives or irrelevant lines for the detection of the playing field. Finally, a brief implementation is documented for a specific use case based on the elimination of the perspective effect in the image, achieving an image result in a two-dimensional plane, from which a wide field of research and usefulness for different areas of the football world is opened such as clubs, journalists, analysts, etc...Depto. de Sistemas Informáticos y ComputaciónFac. de InformáticaTRUEunpu

Tracking Pemain Sepakbola Menggunakan Metode Kalman Filter Berbasis Two-Stages Hungarian Algorithm

Tracking atau pelacakan pemain dalam video sepakbola menjadi bagian penting dalam aplikasi cerdas yang berbasis interaksi manusia dan computer. Dimana dalam proses ini obyek diberikan label sesuai dengan identitasnya atau peran dalam pertandingan. Proses ini bertujuan untuk membantu mencari obyek (pemain atau bola) secara efisien. Kemudian hasil lokasi pergerakan obyek tersebut disimpan dalam media, agar dapat digunakan untuk merekonstruksi pola tersembunyi dari pergerakan obyek. Tantangan utama dalam penelitian tracking ini adalah ketika obyek yang diambil memiliki ukuran kecil, jumlahnya banyak dan memiliki pergerakan yang random, terdapat bayangan oleh karena sistem pencahayaan dan posisi pemain sering berhimpitan (oklusi) sehingga menyulitkan detektor mendeteksi pemain. Peneliti telah berhasil menghadapi tantangan tersebut dengan membuat sistem komprehensif gabungan dua proses, yaitu proses deteksi obyek dan proses tracking. Pada proses deteksi obyek peneliti menggunakan metode background subtraction dengan menambahkan filter operasi bitwise sebagai perekonstruksi obyek dan penghilang bayangan. Selanjutnya, pada proses tracking, metode Kalman filter diaplikasikan dengan menambahkan metode penugasan dual-Hungarian pada proses estimasi obyek dan pemulihan garis trayektori akibat dari oklusi. ================================================================================= Tracking of players becomes an important part of intelligent applications based on human and computer interactions on soccer video. In this process the object is labeled according to its identity or role in the match. This process aims to efficiently locate the players automatically. It is also being used for storing the location for semantic approach. Thus, it can use to reconstruct the hidden patterns of object movement. The main challenge in this tracking are the object taken has a small size, number is large and has a random movement, there are shadows because of lighting system and position of players often coincide (occlusion). Thus, it is difficult for detectors to detect the players. We have successfully faced these challenges by creating a comprehensive system of combined two processes, namely object detection and tracking process. In object detection process, we used background subtraction method by adding bitwise operation filter as object reconstruction and shadow removal. Furthermore, in the tracking process, the Kalman filter method was applied using dual-Hungarian assignment method on the object estimation process and the result of occluded trajectory line