• Title/Summary/Keyword: Anchor Shot Detection

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A New Anchor Shot Detection System for News Video Indexing

  • Lee, Han-Sung;Im, Young-Hee;Park, Joo-Young;Park, Dai-Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.1
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    • pp.133-138
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    • 2008
  • In this paper, we propose a novel anchor shot detection system, named to MASD (Multi-phase Anchor Shot Detection), which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) one class SVM module for determining the anchor shots using a support vector data description. Besides the qualitative analysis, our experiments validate that the proposed system shows not only the comparable accuracy to the recently developed methods, but also more faster detection rate than those of others.

Rule-Based Anchor Shot Detection Method in News Video: KBS and MBC 9 Hour News Cases (규칙기반 뉴스 비디오 앵커 TIT 검출방법: KBS와 MBC 9시 뉴스를 중심으로)

  • Yoo, Hun-Woo;Lee, Myung-Eui
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.1
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    • pp.50-59
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    • 2007
  • In this paper, an anchor shot detection method, which is a basic technology for managing news videos for index and retrieval purposes is proposed. To do that, two most popular news program such as 'KBS 9 Hour News' and 'MBC 9 Hour News' are analyzed and 4-step rule based detection method is proposed First, in the preprocessing, video shot boundaries are detected and the 1st frame of each shot is extracted as a key frame. Then, the detected shot is declared as an anchor shot, if all the following 4 conditions are satisfied. 1) There is an anchor face in the key frame of a shot. 2) Spatial distribution of edges in the key frame is adequate. 3) Background color information of the key frame is similar to the color information of an anchor model. 4) Motion rate in the shot is low. In order to show the validity of the proposed method, three 'KBS 9 Hour News' and three 'MBC 9 Hour News', which have total running time of 108 in minute and are broadcasted at different days, are used for experiments. Average detection rates showed 0.97 in precision, 1.0 in recall, and 0.98 in F-measure.

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A New Anchor Shot Detection System for News Video Indexing

  • Lee, Han-Sung;Im, Young-Hee;Park, Joo-Young;Park, Dai-Hee
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.217-220
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    • 2007
  • In this paper, we present a new anchor shot detection system which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) anchor shot detection module using a support vector data description. According to our computer experiments, the proposed system shows not only the comparable accuracy to the recent other results, but also more faster detection rate than others.

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Anchor Frame Detection Using Anchor Object Extraction (앵커 객체 추출을 이용한 앵커 프레임 검출)

  • Park Ki-Tae;Hwang Doo-Sun;Moon Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.3 s.309
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    • pp.17-24
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    • 2006
  • In this paper, an algorithm for anchor frame detection in news video is proposed, which consists of four steps. In the first step, the cumulative histogram method is used to detect shot boundaries in order to segment a news video into video shots. In the second step, skin color information is used to detect face regions in each shot boundary. In the third step, color information of upper body regions is used to extract anchor object, which produces candidate anchor frames. Then, from the candidate anchor frames, a graph-theoretic cluster analysis algorithm is utilized to classify the news video into anchor-person frames and non-anchor frames. Experiment results have shown the effectiveness of the proposed algorithm.

Multi-modal Detection of Anchor Shot in News Video (다중모드 특징을 사용한 뉴스 동영상의 앵커 장면 검출 기법)

  • Yoo, Sung-Yul;Kang, Dong-Wook;Kim, Ki-Doo;Jung, Kyeong-Hoon
    • Journal of Broadcast Engineering
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    • v.12 no.4
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    • pp.311-320
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    • 2007
  • In this paper, an efficient detection algorithm of an anchor shot in news video is presented. We observed the audio visual characteristics of news video and proposed several low level features which are appropriate for detecting an anchor shot in news video. The overall structure of the proposed algorithm is composed of 3 stages: the pause detection, the audio cluster classification, and the matching with motion activity stage. We used the audio features as well as the motion feature in order to improve the indexing accuracy and the simulation results show that the performance of the proposed algorithm is quite satisfactory.

News Video Shot Boundary Detection using Singular Value Decomposition and Incremental Clustering (특이값 분해와 점증적 클러스터링을 이용한 뉴스 비디오 샷 경계 탐지)

  • Lee, Han-Sung;Im, Young-Hee;Park, Dai-Hee;Lee, Seong-Whan
    • Journal of KIISE:Software and Applications
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    • v.36 no.2
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    • pp.169-177
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    • 2009
  • In this paper, we propose a new shot boundary detection method which is optimized for news video story parsing. This new news shot boundary detection method was designed to satisfy all the following requirements: 1) minimizing the incorrect data in data set for anchor shot detection by improving the recall ratio 2) detecting abrupt cuts and gradual transitions with one single algorithm so as to divide news video into shots with one scan of data set; 3) classifying shots into static or dynamic, therefore, reducing the search space for the subsequent stage of anchor shot detection. The proposed method, based on singular value decomposition with incremental clustering and mercer kernel, has additional desirable features. Applying singular value decomposition, the noise or trivial variations in the video sequence are removed. Therefore, the separability is improved. Mercer kernel improves the possibility of detection of shots which is not separable in input space by mapping data to high dimensional feature space. The experimental results illustrated the superiority of the proposed method with respect to recall criteria and search space reduction for anchor shot detection.

Semantic Scenes Classification of Sports News Video for Sports Genre Analysis (스포츠 장르 분석을 위한 스포츠 뉴스 비디오의 의미적 장면 분류)

  • Song, Mi-Young
    • Journal of Korea Multimedia Society
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    • v.10 no.5
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    • pp.559-568
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    • 2007
  • Anchor-person scene detection is of significance for video shot semantic parsing and indexing clues extraction in content-based news video indexing and retrieval system. This paper proposes an efficient algorithm extracting anchor ranges that exist in sports news video for unit structuring of sports news. To detect anchor person scenes, first, anchor person candidate scene is decided by DCT coefficients and motion vector information in the MPEG4 compressed video. Then, from the candidate anchor scenes, image processing method is utilized to classify the news video into anchor-person scenes and non-anchor(sports) scenes. The proposed scheme achieves a mean precision and recall of 98% in the anchor-person scenes detection experiment.

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Design and Implementation of a news Archive System using Shot Types (샷의 타입을 이용한 뉴스 아카이브 시스템의 설계 및 구현)

  • Han, Keun-Ju;Nang, Jong-Ho;Ha, Myung-Hwan;Jung, Byung-Hee;Kim, Kyeong-Soo
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.5
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    • pp.416-428
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    • 2001
  • In order to build a news archive system. the news video stream should be first segmented into several articles, ad their contents are abstracted effectively. This abstraction helps the users to understand the contents of the article without playing the whole video stream. This paper proposes a new article boundary detection scheme for the news video streams together with a new news article abstraction scheme using the shot types of the news video data. The shots in the news video are classified into anchor person shots, interview shots, speech shots, reporting shots, graphic shots, and others. Since the news article starts with an anchor shot whose duration is relatively longer than other shots with special screen structure, the article boundary in detected by the computing the length of the shot and checking the screen structure in the proposed scheme. For the effective abstraction of the article video, the graphic image located in the right-top of the anchor shot frames is primarily used in the proposed abstraction scheme since it is the abstraction of the article made by the producer of the news according to its contents so that it contains a lot of meaningful information. The key frames of the other shots except interview and report shots are also used to abstract the contents of the articles in the proposed scheme. Upon experimental results, the precision and recall values of the proposed article boundary detection scheme could be 92% and 96%, respectively. This paper also presents a design and implementation of a prototype news archive system on WWW that consists of an indexing tool, an authoring tool, a database for meta-data of the news, and a browsing tool.

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Efficient Detection of Scene Change and Anchorperson Frame in News Video (뉴스 비디오에서의 효율적인 장면 전환과 앵커 화면 검출)

  • Kang, Hyunchul;Lee, Jin-Sung;Lee, Wanjoo
    • Journal of KIISE:Software and Applications
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    • v.32 no.12
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    • pp.1157-1163
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    • 2005
  • In this paper, an efficient and fast method to segment a video in the MPEG(motion picture expert group) video stream is proposed. For the real time processing of large amount of broadcasting data, we use DC images of I-frames in an MPEG compressed video with minimal decoding. Using the modified histogram comparison which counts on not only luminance but also chrominance information, the scene change detection was performed in the fast and accurate way Also, to discriminate anchorperson frame from non-anchor frame, a neural network method was introduced.