| Summary: | 博士 === 國立交通大學 === 資訊科學與工程研究所 === 98 === The explosive proliferation of multimedia data in education, entertainment, sport and various applications necessitates the development of multimedia application systems and tools. As important multimedia content, sports video has been attracting considerable research efforts due to the commercial benefits, entertainment functionalities and a large audience base. The majority of existing work on sports video analysis focuses on shot classification and highlight extraction. However, more keenly than ever, increasing sports fans and professionals desire computer-assisted sports information retrieval. Even more, the umpires demand assistance in judgment with computer technologies. In this thesis, we concentrate on the feature integration and semantic analysis for sports video content understanding, indexing, annotation and retrieval from single camera video.
In sports games, important events are mainly caused by the ball-player interaction and the ball trajectory contains significant information and semantics. To infer the semantic and tactical content, we first propose an efficient and effective scheme to track the ball and compute the ball positions over frames. Ball tracking is arduous task due to the fast speed and small size. It is almost impossible to distinguish the ball within a single frame. Hence, we utilize the ball motion characteristic over frames to identify the true ball trajectory, instead of recognizing which object is the ball in each frame. To retrieve more information about the games and have a further insight, we design an innovative approach of 3D ball trajectory reconstruction in single camera video for court sports, where the court lines and feature objects captured in the frames can be used for camera calibration to compute the transformation between the 3D real world and the 2D frame. The problem of 2D-to-3D inference is intrinsically challenging due to the loss of the depth information in picture capturing. Incorporating the 3D-2D transformation and the physical characteristic of ball motion, we are able to approximate the depth information and accomplish the 2D-to-3D trajectory reconstruction. Manifold applications of sports video understanding and sports information retrieval can be achieved on the basis of the obtained 2D trajectory and the reconstructed 3D trajectory, such as shooting location estimation in basketball, event detection in volleyball, pitch analysis in baseball, etc. The 3D virtual replay generated from the 3D trajectory makes game watching a whole new experience that the audience are allowed to switch between different viewpoints for watching the ball motion.
In baseball, the pitch location (the relative location of the ball in/around the strike zone when the ball passes by the batter) is an important factor affecting the motion of the ball hit into the field. Strike zone provides the reference for determining the pitch location. Hence, we design a contour-based strike zone shaping and visualization method. No matter the batter is right- or left-handed, we are able to shape the strike zone adaptively to the batter’s stance. Computer-assisted strike/ball judgment can also be achieved via the shaped strike zone. In addition to the pitcher/batter confrontation, the defense process after the ball is batted also attracts much attention. Therefore, we design algorithms to recognize spatial patterns in frames for classifying the active regions of event occurrence in the field. The ball routing patterns and defense process can be inferred from the transitions of the active regions captured in the video. Furthermore, the sequences with similar ball routing and defense patterns can be retrieved for defense strategy analysis.
Comprehensive experiments on basketball, volleyball and baseball videos have been conducted to evaluate the performance of the proposed methods. The experimental results show that the proposed methods perform well in retrieving game information and even reconstructing 3D information from single camera video for different kinds of sports. It is our belief that the preliminary work in this thesis will lead to satisfactory solution for sports information retrieval, content understanding, tactics analysis and computer-assisted game study in more kinds of sports videos.
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