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We aim to develop an automatic contents production system of soccer video commentary based on digital shooting techniques, which consists of digital camera work and digital switching technique. Digital camera work is defined as virtual panning and virtual zooming. Virtual panning is a video production technique of clipping a fixed size frame and then controlling the frame location on a high definition material video. Virtual zooming is a video production technique of clipping a frame and then controlling frame size. Also, digital switching is defined as the change in virtual cameras by controlling the rapid change of frame location or size on a high definition material video. We describe a method of digital camera work that focused on players and a ball as a sub-system of an automatic contents production system for soccer video commentary. This study uses analytic hierarchy process to carry out subjective evaluation of the produced video contents with digital camera work.

Video editing is used to produce a final version with a specific duration by finding and selecting appropriate shots from the raw video material and connecting them. Video editing process is generally conducted according to the special rules called “video grammar” in order to produce excellent and intelligible videos for broadcasting. However, this editing consumes a lot of human editor's working time. To solve this problem, an efficient and new video editing technique or system is required. The goal of this study is to develop an intelligent support system for video editing based on video grammar. This paper proposes a method of using camerawork density, camerawork instability, and cut point parameters to automatically segment the raw video materials into useful sections and useless sections. The method is based on video grammar as a part of the video editing support system.

In this paper, we propose an online training-oriented video shooting navigation system focused on camerawork based on video grammar by real-time camerawork evaluation to train users shooting nice shots for the later editing work. In this system, the processing speed must be very high so that we use a luminance projection correlation and a structure tensor method to extract the camerawork parameters in real-time. From the results of camerawork analysis, the results of each frame are classified into 7 camerawork types and the system issues 6 types of alarms and navigates users along the specified shot depending on camerawork based on video grammar in real-time while shooting the shot. Thereby, users can naturally acquire shooting style by trying to decrease alarms of improper camerawork without a consideration of the video grammar.

We are studying about automatic production of soccer sports videos for easy understanding by using digital camera work on camera fixed videos. The digital camera work is a movie technique which uses virtual panning and zooming by clipping frames from hi-resolution images and controlling the frame size and position. We have studied so far digital panning. In this paper, we propose a method of digital zooming by automatically recognizing the game situation or events such as penalty kick and free kick based on player and ball tracking. These recognition results are used as key indices to retrieve the event scenes from soccer videos. We compared the proposed technique with a conventional technique by AHP method that can reflect an individual subjectivity.

In this paper, we propose a video shooting navigation system by real-time useful shot discrimination based on video grammar to support users shooting nice shots for later editing work. In this system, the processing speed must be very high so that we use a gray value projection method to extract the camerawork parameters in real-time. From the result of camerawork and gray value analysis, the shots are classified into 16 states and the system issues alarms and instructions about the usefulness and uselessness of the shots in real-time just after shooting the shot. Thereby, users can retake a shot necessary for later editing efficiently

To deliver baseball highlight scenes broadcast live to baseball fans outside, image processings such as an online video analyzing, meta information extraction and automatic editing have to be performed in real time. This paper proposes a high-speed image processing to automatically extract PC (pitcher and catcher) scenes, based on feature mining, from a baseball live game broadcast in real time as a part of the baseball highlight scene delivery system. This method showed 95.5% accuracy in the F-measure score within 1/30 of real time.

We aim at the realization of automatic adaptive contents production system of commentary soccer video based on digital shooting technique which is composed of digital camera work and digital switching technique for small audience such as a fellow some enthusiast and a individual. The digital camera work is defined as virtual panning and virtual zooming. Also, the digital switching is defined as the change of some virtual camera by controlling rapid change of frame location or size on a HD(high definition) material video. In this paper, we describe a method of digital camera work technique focused on players and a ball as a sub-system of automatic contents production system for commentary soccer video. The produced video contents with digital camera work is subjectively evaluated by AHP (Analytic Hierarchy Process).