• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.567-571
• /
• 2009

Sports game broadcasting system uses multiple video cameras in order to offer exciting and dynamic scenes for the TV audiences. Since, however, the traditional broadcasting system edits the multiple views into a static video stream, it is difficult to provide the intelligent broadcasting service that summarizes or retrieves specific scenes or events based on the user preference. In this paper, we propose the summarization and retrieval system for the soccer videos based on multiple cameras. It extracts the highlights such as shot on goal, crossing, foul, and set piece using dynamic Bayesian network based on soccer players' primitive behaviors annotated on videos, and selects a proper view for each highlight according to its type. The proposed system, therefore, offers users the highlight summarization or preferred view selection, and can provide personalized broadcasting services by considering the user's preference.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.517-518
• /
• 2024

본 연구에서는 특정 비디오에서 추출된 비디오 클립이 어떤 비디오에서 추출된 것인지 탐색하는 알고리즘을 제안한다. 국내 이스포츠 리그 중 하나인 LCK의 경기 영상과 하이라이트 영상을 수집하여 알고리즘의 성능을 테스트하였다. 본 연구에서 제안한 알고리즘은 하이라이트 비디오 추출 모델개발에 필요한 비디오-하이라이트 클립 데이터셋을 구축하는 데 도움이 될 것이라 기대한다.

• Journal of Broadcast Engineering
• /
• v.23 no.2
• /
• pp.218-226
• /
• 2018

As the number of personal broadcasting contents is rapidly increasing, the demand for a service that provides highlights is growing. A highlight, a collection of interesting scenes, can improve the quality of viewing experience. In this paper, we propose a method to automatically detect highlights using only chat traffic information. We also propose evaluation methods the effectiveness of using chat traffic in highlight detection. We apply the detection algorithm to game broadcasting, which has larger audience, and demonstrate its performance.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.5 s.37
• /
• pp.65-76
• /
• 2005

A digital video is a very long data that requires large-capacity storage space. As such, prior to watching a long original video, video watchers want to watch a summarized version of the video. In the field of sports, in particular, highlights videos are frequently watched. In short, a highlights video allows a video watcher to determine whether the highlights video is well worth watching. This paper proposes a scheme for creating soccer video highlights using the structural features of captions in terms of time and space. Such structural features are used to extract caption frame intervals and caption keyframes. A highlights video is created through resetting shots for caption keyframes, by means of logical indexing, and through the use of the rule for creating highlights. Finally, highlights videos and video segments can be searched and browsed in a way that allows the video watcher to select his/her desired items from the browser.

• Journal of the Institute of Convergence Signal Processing
• /
• v.14 no.4
• /
• pp.231-234
• /
• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

• The KIPS Transactions:PartB
• /
• v.8B no.4
• /
• pp.411-418
• /
• 2001

비디오 하이라이트(highlights)는 원래의 비디오 보다 짧고 많은 양의 의미를 갖는다. 기존의 파노라마 형태의 추상화 기법은 여러 프레임을 하나의 프레임으로 모자이크하는 형태이었고, TV 드라마 하이라이트 방법은 카메라의 이동이나 특수효과에 의존하기 때문에 스포츠 비디오에 적용은 부적합하다. 이 논문에서는 축구 비디오를 대상으로 시각정보와 자막을 이용하는 새로운 비디오 하이라이트 생성 방법과 이벤트 기반 비디오 인덱싱 방법을 제안한다. 하이라이트 생성은 하이라이트 생성 규칙에 따라 자막에 의해 추출된 TIT을 중심으로 시각정보에 의해 추출된 샷을 합성하여 생성하였고, 인덱싱은 자막으로 추출된 샷은 주요소로, 시각정보에 의해 추출된 샷은 부가적 요소로 구성하였다. 실험에서는 샷 추출기법 중 대표적인 컬러히스토그램과 $\chi$$^2$히스토그램과의 성능을 비교하여 제안한 하이라이트 기법이 다른 방식보다 우수함을 증명하였다.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.45-53
• /
• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• Journal of Korea Multimedia Society
• /
• v.7 no.11
• /
• pp.1540-1549
• /
• 2004

In this paper, we propose an algorithm to detect semantic events in golf video using Hidden Markov Model. The purpose of this paper is to identify and classify the golf events to facilitate highlight-based video indexing and summarization. In this paper we first define 4 semantic events, and then design HMM model with states made up of each event. We also use 10 multiple visual features based on MPEG-7 visual descriptors to acquire parameters of HMM for each event. Experimental results showed that the proposed algorithm provided reasonable detection performance for identifying a variety of golf events.

• Proceedings of the IEEK Conference
• /
• 2000.11c
• /
• pp.81-84
• /
• 2000

In this paper, we propose an efficient method to extract a goal area which may be closely related to the scoring highlight. In our method, the boundary between the ground and the non-ground area is used. An efficient methods for a rapid detection of both the boundary and then the goal area are proposed. Our simulation results show that our method is very reliable and takes less processing time compared with previous methods. This performance improvements may be caused by the use of a general simple feature.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.11a
• /
• pp.619-623
• /
• 2002

We can speak caption as information that can not except caption on sports video. The sports highlight were composed that we recognize captioning. This paper is the necessary work to the middle-step to analysis the caption through the retrieval and discrimination from the position of caption. This paper improve at first and simplify the image through the excellent threshold value algorithm in the preprocessing and then use method that can analysis caption through the multiplex frame merging algorithm. Its speed performing shows up higher and simplier than the region growing process.