A Robust Superimposed Caption Box Content Understanding for Sports Videos

Shih, Huang-Chia; Huang, Chung‐Lin

doi:10.1109/ism.2006.11

Cited by 8 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The above methods perform well as far as there is only one caption in a scene and it is regarded as a scorebox. In this sense, the proposed method in [6] can be a good solution. They treat the caption box based on the assumption that there is high color correlation and low motion activities within the caption box.…”

Section: Introductionmentioning

confidence: 90%

Scorebox extraction from mobile sports videos using Support Vector Machines

Kim

Park

Kim

2008

Applications of Digital Image Processing XXXI

View full text Add to dashboard Cite

Scorebox plays an important role in understanding contents of sports videos. However, the tiny scorebox may give the small-display-viewers uncomfortable experience in grasping the game situation. In this paper, we propose a novel framework to extract the scorebox from sports video frames. We first extract candidates by using accumulated intensity and edge information after short learning period. Since there are various types of scoreboxes inserted in sports videos, multiple attributes need to be used for efficient extraction. Based on those attributes, the optimal information gain is computed and top three ranked attributes in terms of information gain are selected as a three-dimensional feature vector for Support Vector Machines (SVM) to distinguish the scorebox from other candidates, such as logos and advertisement boards. The proposed method is tested on various videos of sports games and experimental results show the efficiency and robustness of our proposed method.

show abstract

Section: Introductionmentioning

confidence: 90%

Scorebox extraction from mobile sports videos using Support Vector Machines

Kim

Park

Kim

2008

Applications of Digital Image Processing XXXI

View full text Add to dashboard Cite

show abstract

“…For example, Assfalg et al [34,88] defined heuristic rules to detect caption, e.g., the caption must remain stable for a period of time for the audience to read, and caption should have high luminance contrast, etc; Mihajlovic et al [40] applied horizontal differential filtering to locate the caption area from shaded area and use pattern matching to recognize the caption text to detect highlights from Formula 1 race video; Chen et al [89] used SVM to identify single text line in video frames and perform Optical Character Recognition (OCR) for text recognition; Zhang et al [90] proposed to detect the caption text change event to identify "score" and "last pitch" event in baseball game; Li et al [91] used Connected Component Analysis to segment the caption area and detected the periodicity of caption text change to recognize the superimposed game clock time. Shih et al [92] introduced a robust caption extraction, localization, recognition, and interpretation method to understand the game score, team name, etc game semantics.…”

Section: Caption Text Recognitionmentioning

confidence: 99%

Content-based sports video analysis and composition

Wang¹

View full text Add to dashboard Cite

This thesis proposes solutions for content-based sports video analysis, including multimodal feature extraction, middle-level representation and semantic event detection. In addition, solutions for sports video composition and personalization are also examined. The first part of the thesis describes our methodology to detect semantic events and event boundaries from both broadcast sports video and non-broadcast sports video. Specifically, to process broadcast sports video, our approach not only uses visual/audio features, we also analyze the web-casting text information associated with the video and synchronize it with the visual/audio features to detect event, locate event boundaries and identify involved players/teams; To process non-broadcast sports video, we select the raw unedited main-camera soccer video as the input and use visual, audio and motion features extraction with multi-level modeling to detect event and event boundaries. Our proposed techniques are evaluated using large sports video data set and achieved satisfactory user acceptance score. The second part of the thesis introduces three novel applications based on our proposed sports video analysis techniques. The first application is a live sports highlight generation system which can automatically detect multiple events from a live sports game and extract a suitable video segment for each event to provide live and personalized game viewership via various mediums. The second application attempts to automatically generate broadcast soccer video composition from multiple raw video captures by detecting events from unedited soccer video and mimicking human director's practice to control the replay insertion and camera view switching operations. The third application is a personalized music sports video generation system to automatically select and align desired sports video scenes with music clips to generate music video clips. The three proposed systems are tested using objective evaluations and subjective user studies. i ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library Many people have contributed their ideas, time, and energy in my pursuit of this PhD research. I wish it was possible to thank them all. First thanks must go to my supervisor, Dr. Chng Eng Siong, and co-supervisor, Dr. Xu Chang Sheng, who have been truly inspirational throughout my candidature. I would like to thank them for all their guidance, rewarding discussions, cooperation, encouragements, and lasting support to my study and my life. I have been blessed to find in them all the good qualities of a supervisor. I am indebted to the School of Computer Engineering, Nanyang Technology University (NTU), for offering me the PhD scholarship. I am also thankful to the Institute for Infocomm Research (I 2 R) and the Centre for Multimedia and Network Technology, NTU for providing me an excellent working environment with all the much needed facilities and services, as well as financial supports including travel allowances....

show abstract