• Journal of KIISE:Software and Applications
• /
• v.33 no.10
• /
• pp.851-861
• /
• 2006

The paper proposes a novel unsupervised video object segmentation algorithm for image sequences with low depth-of-field (DOF), which is a popular photographic technique enabling to represent the intention of photographer by giving a clear focus only on an object-of-interest (OOI). The proposed algorithm largely consists of two modules. The first module automatically extracts OOIs from the first frame by separating sharply focused OOIs from other out-of-focused foreground or background objects. The second module tracks OOIs for the rest of the video sequence, aimed at running the system in real-time, or at least, semi-real-time. The experimental results indicate that the proposed algorithm provides an effective tool, which can be a basis of applications, such as video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing systems.

• 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.

• Journal of Korean Library and Information Science Society
• /
• v.31 no.1
• /
• pp.229-258
• /
• 2000

The growth of digital image an video archives is increasing the need for tools that efficiently search through large amount of visual dta. Retrieval of visual data is important issue in multimedia database. We are using contented-based visual data retrieval method for efficient retrieval of visual data. In this paper, we introduced fundamental techniques using characteristic values of image data and indexing techniques required for content-based visual retrieval. In addition we introduced content-based visual retrieval system for use of digital library.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1999.11b
• /
• pp.141-145
• /
• 1999

뉴스나 드라마, 영화 등의 비디오에 대한 검색 시 일반 사용자의 요구에 가장 잘 부합되는 결과를 얻기 위해 비디오 데이터의 의미적 분석과 색인을 만드는 것이 필요하다. 일반적으로 음성신호가 비디오 데이터의 내용을 잘 나타내고 비디오와 동기가 이루어져 있으므로, 내용기반 검색을 위한 비디오 데이터 분할에 효율적으로 이용될 수 있다 본 논문에서는 캡션 정보가 주어지는 방송뉴스 프로그램을 대상으로 효율적인 검색, 색인을 위한 비디오 데이터의 분할에 음성인식기술을 적용하는 방법을 제안하고 그에 따른 실험결과를 제시한다.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 2006.07a
• /
• pp.459-459
• /
• 2006

• Proceedings of the IEEK Conference
• /
• 2001.06d
• /
• pp.101-104
• /
• 2001

This paper proposes a unique shot boundary detection algorithm for the video indexing and/or browsing. Conventional methods based on the frame differences and the histogram differences are improved. Instead of using absolute frame differences, block by block based relative frame differences are employed. Frame adaptive thresholding values are also employed for the better detection. for the cases that the frame differences are not enough to detect the shot boundary, histogram differences are selectively applied. Experimental results show that the proposed algorithm reduces both the “false positive” errors and the “false negative” errors especially for the videos of dynamic local and/or global motions

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1999.06b
• /
• pp.109-114
• /
• 1999

동영상을 효율적으로 검색하기 위해서 동영상을 장면 단위로 분할하는 과정이 필요하다 이 논문에서는 동영상에서 장면이 전환되는 지점을 빠르게 검출하는 방법을 제안한다. 먼저 MPEG 압축 영상에 대하여 시간적 표본화를 통하여 추출된 압축 영역의 데이터를 사용하여 장면 전환의 후보 구간들을 정하고, 다음으로 이들 구간 안에서 각 프레임의 화소값을 얻고, 이를 사용하여 정확한 장면 전환 지점을 찾아낸다. 제안된 방법은 빠른 검출 속도와 함께 높은 정확성을 갖는다. 또한 카메라 플래시 때문에 장면 전환으로 잘못 검출되는 것을 방지할 수 있는 방법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1998.05a
• /
• pp.222-226
• /
• 1998

뉴스 비디오 데이터베이스를 구축하기 위해서는 비디오 색인의 자동화에 관한 연구가 필연적이다. 그리하여, 본 논문에서는 비디오 색인화를 자동화 하는 방법으로, 이전에 제안한 키 프레임(key frame)의 추출 방법을 이용하여 추출된 키 프레임을 대상으로 색인화 하였다. 즉, 추출된 키 프레임 중에서 메타 색인에 해당하는 앵커 프레임(anchor frame)을 선택하는 방법을 제시하고, 선택된 앵커 프레임을 이용하여 뉴스 비디오를 색인화 하였다. 구현된 비디오 색인화는 사용자의 관점에 따라 여러 가지 방법으로 브라우징(browsing)되며, 사용자가 원하는 뉴스 비디오 씬(scene)들을 쉽게 선택하여 볼 수 있는 특징을 제공하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.4
• /
• pp.95-102
• /
• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.

• Journal of the Korea Computer Industry Society
• /
• v.5 no.2
• /
• pp.203-216
• /
• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.