An automatic news video parsing, indexing and browsing system

Low, Chien Yong; Tian, Qi; Zhang, Hong-Jiang

doi:10.1145/244130.244453

Cited by 23 publications

(6 citation statements)

References 2 publications

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“…Companies like Virage [22] and MediaSite [12] are currently providing these services for finding video on the Internet. Others have used domain knowledge to improve these services for specific video content types like news [11]. Such work focuses on query-based searching of collections of video content rather than on browsing an individual video that is the focus of this study.…”

Section: Related Workmentioning

confidence: 99%

Browsing digital video

Gupta

Sanocki

et al. 2000

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

110

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Video in digital format played on programmable devices presents opportunities for significantly enhancing the user's viewing experience. For example, time compression and pause removal can shorten the viewing time for a video, textual and visual indices can allow personalized navigation through the content, and random-access digital storage allows instantaneous seeks into the content. To understand user behavior when such capabilities are available, we built a software video browsing application that combines many such features. We present results from a user study where users browsed video in six different categories: classroom lectures, conference presentations, entertainment shows, news, sports, and travel. Our results show that the most frequently used features were time compression, pause removal, and navigation using shot boundaries. Also, the behavior was different depending on the content type, and we present a classification. Finally, the users found the browser to be very useful. Two main reasons were: i) the ability to save time and ii) the feeling of control over what content they watched.

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Section: Related Workmentioning

confidence: 99%

Browsing digital video

Gupta

Sanocki

et al. 2000

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

110

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show abstract

“…As a consequence of all this structure, it is relatively easy to give a machine the understanding of commands such as "skip ahead to the sports section" without the need to understand all the pixels in every image of the video sequence. This has made the topic of analyzing newscasts a very popular one in the video databases literature [3], [20], [26], [55].…”

Section: Video Structurementioning

confidence: 99%

Statistical models of video structure for content analysis and characterization

Vasconcelos

Lippman

2000

IEEE Trans. on Image Process.

108

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Abstract-Content structure plays an important role in the understanding of video. In this paper, we argue that knowledge about structure can be used both as a means to improve the performance of content analysis and to extract features that convey semantic information about the content. We introduce statistical models for two important components of this structure, shot duration and activity, and demonstrate the usefulness of these models with two practical applications. First, we develop a Bayesian formulation for the shot segmentation problem that is shown to extend the standard thresholding model in an adaptive and intuitive way, leading to improved segmentation accuracy. Second, by applying the transformation into the shot duration/activity feature space to a database of movie clips, we also illustrate how the Bayesian model captures semantic properties of the content. We suggest ways in which these properties can be used as a basis for intuitive content-based access to movie libraries.Content structure plays an important role in the understanding of video. In this paper, we argue that knowledge about structure can be used both as a means to improve the performance of content analysis and to extract features that convey semantic information about the content. We introduce statistical models for two important components of this structure, shot duration and activity, and demonstrate the usefulness of these models with two practical applications. First, we develop a Bayesian formulation for the shot segmentation problem that is shown to extend the standard thresholding model in an adaptive and intuitive way, leading to improved segmentation accuracy. Second, by applying the transformation into the shot duration/activity feature space to a database of movie clips, we also illustrate how the Bayesian model captures semantic properties of the content. We suggest ways in which these properties can be used as a basis for intuitive content-based access to movie libraries.

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“…Numerous approaches to automation of various steps in news-program analysis were proposed in recent literature (e.g. [1][2][3][4][5][6][7][8][9][10][11][12][13]]). In this paper we present the DANCERS -Delft AdvaNCed nEws Retrieval System -we developed to obtain a complete and reliable topic-based organization of a news archive with minimized user intervention.…”

Section: Introductionmentioning

confidence: 99%

<title>DANCERS: Delft advanced news retrieval system</title>

et al. 2001

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In this paper we present a system for automated analysis, classification and indexing of broadcast news programs. The system first analyzes the visual and the speech stream of an input news program in order to obtain an initial partitioning of the program into the so-called report segments. The analysis of the visual stream provides the boundaries of the report segments lying at the beginning and the end of each anchorperson shot. This analysis step is performed by applying an existing technique for anchorperson shot detection. The analysis of the speech stream gives the boundaries of the report segments lying in the middle of each (sufficiently long) silent interval. Then, the transcribed speech of each of the report segments is matched with the content of a large pre-specified textual topic database. This database covers a large number of topics and can be updated by the user at any time. For each topic a vast number of keywords is given, each of which is also assigned a weight that indicates the importance of a keyword for a certain topic. The result of the matching procedure is a list of probable topics per report segment, where for each topic on the list a likelihood is computed based on the number of relevant keywords found in the segment and on the weights of those keywords. The list of topics per segment is then shortened by separating the most probable from least probable topics based on their likelihood. Finally, the likelihood values of the most probable topics are used in the last system module to merge related neighboring segments into reports. The most probable topics serving as the base for the segment-merging procedure are at the same time the retrieval indexes for the reports and are used for classifying together all reports in the database that cover one and the same topic.

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An automatic news video parsing, indexing and browsing system

Cited by 23 publications

References 2 publications

Browsing digital video

Browsing digital video

Statistical models of video structure for content analysis and characterization

<title>DANCERS: Delft advanced news retrieval system</title>

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