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We have improved a previously reported method for extracting and judging camerawork for an online training-oriented video-shooting navigation system.It uses video grammar for evaluating user's high-speed camerawork to assist them in effectively shooting video that can be easily edited.High-speed processing is required in the navigation system,so we use a luminance-projection correlation method to extract the camerawork parameters at high speed.However,the accuracy is insufficient.To improve the accuracy,we combined the luminance-projection correlation method with a split tensor histogram method that classifies each frame into one of seven camerawork types.Camerawork analysis results showed that the accuracy was significantly improved.

We aim to develop a video-shooting learning system using video grammar and a real-time,on- and offline navigation system.As an initial step,we have developed an online navigation system that uses video grammar for evaluating users' high-speed camerawork to assist them with effectively shooting shots that can be easily edited.Previous camerawork analysis results showed that by classifying each frame into one of seven camerawork types,high-speed processing accuracy is improved.The system issues three types of alarms depending on the camerawork and the video grammar while a user is shooting that guide the user toward a specified shot.Users thus can naturally acquire a shooting style by trying to decrease the number of alarms and can obtain the specified shot without having to consider the video grammar.

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.

Since the advent of the digital era the lack of video coding has been a problem. In order to resolve this problem, the editing work, which takes the most time during the production of video content, must be made more efficient. In general, broadcast video is set up using video grammar, a set of standard principles used for broadcasting any video content. Therefore, in order to make editing work more efficient, a video editing support system which reflects this video grammar must be developed. In order to create this kind of video editing support system, indexing information must be set up beforehand for the raw video shot by the camera operator so as to take advantage of the video grammar. Within the video grammar the particularly important rules have to do with connecting shots. In this paper the authors propose a method to automatically index shot size, along with proposing a video editing support system based on video grammar. © 2003 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 86(11): 61–71, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.10201

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.

The popularity of cameras with GPS receivers and the emergence of photo-sharing websites such as Flickr have created enormous collections of photos that are annotated with GPS locations, time-stamps, photographers, etc. Thus, one can obtain a large number of observations of where and when people take photos. Since people tend to take photos when they meet visually interesting things on their sightseeing tours, attention has recently been devoted to constructing sightseeing guide systems that exploit the information revealed by the collective behavior of users in photo-sharing websites (see, e.g., [Lu et al. 2010]). Previous work [Crandall et al. 2009] discovered popular photo spots from a large number of geo-tagged photos, and visualized them with the found representative images on maps.

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).

Video editing is the work to produce the final videos with certain duration by finding and selecting appropriate shots from the material videos and connecting them. In order to produce the excellent videos, this process is generally conducted according to the special rules called "video grammar". In this paper, we propose an intelligent support system for the video editing where metadata are extracted automatically and then the video grammars are applied to the extracted metadata.

This paper proposes a method to automatically extract highlight scenes from sports (baseball) live video in real time and to allow users to retrieve them. For this purpose, sophisticated speech recognition is employed to convert the speech signal into the text and to extract a group of keywords in real time. Image processing detects, also in real time, the pitcher scenes and ending at the successive pitcher scene. Highlight scenes are extracted as the pitching sections with the keywords such as home run, two-base hit and three-base hit extracted from speech signals.