• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10c
• /
• pp.41-45
• /
• 2007

The rapid growing of video content production leads to the necessity of developing more complex indexing systems in order to efficiently allow searching, retrieval and presentation of the desired segments of videos. This paper presents a method for indexing soccer video through automatic extraction of information from internet. The proposed paper defines a metadata structure to formally represent the knowledge of soccer matches and provides an automatic method to extract semantic information from web-sites. This approach improves the capability to extract more reliable and richer semantic Information for soccer videos. Experimental results demonstrate that the proposed method provides an efficient performance.

• The KIPS Transactions:PartB
• /
• v.14B no.1 s.111
• /
• pp.1-4
• /
• 2007

In this paper, we propose an efficient scheme for automatically detecting highlight scenes in soccer videos. Highlights are defined as shooting scenes and goal scenes. Through the analysis of soccer videos, we notice that most of highlight scenes are shown around the goal post area. It is also noticed that the TV camera zooms in a setter player or spectators after the highlight stones. Detection of highlight scenes for soccer videos consists of three steps. The first step is the extraction of the playing field using a statistical threshold. The second step is the detection of goal posts. In the final step, we detect a zooming of a soccer player or spectators by using connected component labeling of non-playing field. In order to evaluate the performance of our method, the precision and the recall are computed. Experimental results have shown the effectiveness of the proposed method, with 95.2% precision and 85.4% recall.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.12
• /
• pp.1752-1755
• /
• 2016

In this letter, to determine how mathematical morphology operators can be best used to enhance the accuracy of background subtraction for "soccer videos", we conducted an experimental comparative study. We investigated six different mathematical morphology operators under the same experimental setup. We found that the closing by reconstruction-opening by reconstruction is optimal through the experiments using the F-measure. We believe that this comprehensive comparative study serves as a reference point and guide for developers and practitioners in choosing an appropriate mathematical morphology operator adopted for building intelligent soccer video analysis systems.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.1
• /
• pp.46-49
• /
• 2017

In this letter, we investigate the impact of image downsampling on the performance of background subtraction in Full-HD soccer videos. To this end, we evaluated the performance of background subtraction in terms of both accuracy and computational time. Furthermore, for the sake of completeness, we used two different background subtraction methods under the same experimental setup. For the quantitative comparison, we employed the F-measure and FPS(frames per second). We believe that this study serves as a practically useful benchmark for researchers and practitioners in developing a fast background subtraction algorithm adopted for building real-time intelligent soccer video analysis systems.

• International journal of advanced smart convergence
• /
• v.8 no.2
• /
• pp.88-93
• /
• 2019

This study explores one of charity drive contents on YouTube channel. Due to the advance of science and technology, ordinary people come to make their own video content online, usually via YouTube. YouTube becomes number one online video storage/streaming platform, and many people upload their own video and they get attention and fame. This study analyzes various aspects of Shoot for Love, soccer-based charity drive videos shown on YouTube channel created in South Korea. Unlike popular videos in YouTube, Shoot for Love centers on charity by casting popular soccer players and celebrities. Especially, this study researches 1) Components 2) Traits of Components 3) Contents of Components in Shoot for Love. Throughout this, it not only analyzes unique aspects of Shoot for Love that show how and why YouTube content matters, but also suggest plausible methods to drive charity and institution are suggested that appeal to the public.

• International journal of advanced smart convergence
• /
• v.9 no.3
• /
• pp.28-35
• /
• 2020

YouTube has been gaining popularity all around the world. A lot of companies have created their own YouTube channels to leverage them in diverse ways; they upload commercial videos, show people user reviews, and conduct promotions with their products. Sports clubs are no exception; they upload diverse videos to gain popularity and to interact with their fans. This study analyzes how the English Premier League (EPL) clubs leverage their YouTube channel as soccer (football in European nations) players. YouTube activities of 20 clubs during the 2019/2020 Season are investigated. After careful consideration, we decide to examine two factors of the respective channel of the YouTube: 1) Popularity (the number of views and subscribers) 2) Contents of videos (e.g. interviews and highlight scenes). The study followingly inspects the benefits of utilizing YouTube channels and of direct communication between sports clubs and fans in online settings.

• Journal of Broadcast Engineering
• /
• v.13 no.4
• /
• pp.427-439
• /
• 2008

This paper proposes a novel method to convert monoscopic soccer videos to stereoscopic videos. Through the soccer video analysis process, we detect shot boundaries and classify soccer frames into long shot or non-long shot. In the long shot case, the depth mapis generated relying on the size of the extracted ground region. For the non-long shot case, the shot is further partitioned into three types by considering the number of ground blocks and skin blocks which is obtained by a simple skin-color detection method. Then three different depth assignment methods are applied to each non-long shot types: 1) Depth estimation by object region extraction, 2) Foreground estimation by using the skin block and depth value computation by Gaussian function, and 3)the depth map generation for shots not containing the skin blocks. This depth assignment is followed by stereoscopic image generation. Subjective evaluation comparing generated depth maps and corresponding stereoscopic images indicate that the proposed algorithm can yield the sense of depth from a single view images.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.2
• /
• pp.713-728
• /
• 2021

This paper proposes an augmented reality technique to generate acrobatic scenes from hitting motion videos. After a user shoots a motion that mimics hitting an object with hands or feet, their pose is analyzed using motion tracking with deep learning to track hand or foot movement while hitting the object. Hitting position and time are then extracted to generate the object's moving trajectory using physics optimization and synchronized with the video. The proposed method can create videos for hitting objects with feet, e.g. soccer ball lifting; fists, e.g. tap ball, etc. and is suitable for augmented reality applications to include virtual objects.

• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.671-674
• /
• 2000

In this paper, we present a robust global registration algorithm for multi-frame image mosaics. When we perform a pair-wise registration recovering a projective transformation between two consecutive frames, severe mis-registration among multiple frames, which are not consecutive, can be detected. It is because the concatenation of those pair-wise transformations leads to global alignment errors. To overcome those mis-registrations, we propose a new algorithm using multiple frames for constructing image mosaics. We use a graph to represent the temporal and spatial connectivity and show that global registration can be obtained through the search for an optimal path in the constructed graph. The definition of an adequate objective function characterizing the global registration provides a direct manipulation of the graph. In the presence of moving objects, especially large ones compared with low texture backgrounds, by using the likelihood ratio as the objective function, we can deal with some of the most challenging videos like basketball or soccer Moreover, the algorithm can be parallelized so it can be more efficiently implemented. Finally, we give some experimental results from real videos.