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Recent advance in digital storage technology has enabled us to archive more than 1,700 hours of video data from a daily Japanese news show in the last nine years. In this paper, to effectively make use of the video data in the archive, we first present a news video structuring method based on the chronological semantic relations between stories, na...
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... shown in Fig. 13, besides simply selecting each story, this function allows a user to select stories along a topic thread between two or more specified stories. The interface outputs the selected stories as a list of story/video IDs, which could be exported as an input to a video summarization system, or simply as a play-list for a video editing ...
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Recent advance in digital storage technology has enabled us to archive a
large volume of video data. Thanks to this trend, we have archived more
than 1,800 hours of video data from a daily Japanese news show in the
last ten years. When considering the effective use of such a large news
video archive, we assumed that analysis of its chronological an...
Citations
... The problem with these approaches is that they mainly focus either on the structural extraction of a single news show or try to concatenate the different threads of one news story over time. The combination of different story threads is so far not addressed, though the work of Ide et al. on "medi-aWalker" [10] is the closest reaching into this direction. Its aim is to establish and exploit the chronological semantic structure in a large-scale broadcast news video archive. ...
... As we use particular terms throughout the paper, we first define those. We base the definition of these terms on two sources, namely the Topic Detection and Tracking (TDT) workshop series organized by NIST [6] and the work by Ide et al. [10]. The definitions of the first three adopt TDT's view, while the latter two follow those introduced by Ide et al. ...
... The video data used in our work comes from the NII-TVRECS archive [11], which consists of a Japanese news show recorded daily for more than ten years (1,800-hours). The video data is accompanied with closed-caption, and is segmented into stories by the method described in [10]. ...
One of the common parts of news is to provide the background for a current event, such as the resignation of a Prime Minister. This paper addresses a framework that facilitates semi-automated authoring of explanatory audio-visual news topics in a retrospective style for the domain of politics based on already edited new stories available in the repository of the news corporation. The aim is to facilitate a journalist with an audio-visual body based on which he/she can finalize the explanatory piece. The proposed framework enhances current state of the art video summarization by allowing the combination of different news stories into one coherent explanation about a topic of the current news. The framework introduces techniques that exploit demoscopic data in form of polls for the development of the general story outline; the automatic retrieval of relevant material by using a combination of event templates and automatic news summarization over topic threads; and the generation of the final video by applying a set of trimming rules. Example generations are presented and discussed and an outline of future work is presented.
Existing video search engines return a ranked list of videos for each user query, which is not convenient for browsing the results of query topics that have multiple facets, such as the “early life”, “personal life” and “presidency” of a query “Barack Obama”. Organizing video search results into semantically structured hierarchies with nodes covering different topic facets can significantly improve the browsing efficiency for such kind of queries. In this paper, we introduce a hierarchical visualization approach for video search result browsing, which can help users quickly understand multiple facets of a query topic in a very well organized manner. Given a query, our approach starts from the hierarchy of its textual descriptions normally available on Wikipedia, and then adjusts the hierarchical structure by analyzing video information to reflect the topic structure of the search result. After that, a simple optimization problem is formulated to perform video-to-node association considering three important criteria. Furthermore, additional topic facets are mined to complement the contents of the existing semantic hierarchies. A large YouTube video dataset is constructed to evaluate our approach both quantitatively and qualitatively. A demo system is also developed for users to interact with the proposed browsing approach.
Organizing video search results into semantically structured hierarchies can greatly improve the efficiency of browsing complex query topics. Traditional hierarchical clustering techniques are inadequate since they lack the ability to generate semantically interpretable structures. In this paper, we introduce an approach to organize video search results to an adapted semantic hierarchy. As many hot search topics such as celebrities and famous cities have Wikipedia pages where hierarchical topic structures are available, we start from the Wikipedia hierarchies and adjust the structures according to the characteristics of the returned videos from a search engine. Ordinary clustering based on textual information of the videos is performed to discover the hidden topic structures in the video search results, which are used to adapt the hierarchy extracted from Wikipedia. After that, a simple optimization problem is formulated to assign the videos to each node of the hierarchy considering three important criteria. Experiments conducted on a Youtube video dataset verify the effectiveness of our approach.
Recent advance in digital storage technology has enabled us to archive a
large volume of video data. Thanks to this trend, we have archived more
than 1,800 hours of video data from a daily Japanese news show in the
last ten years. When considering the effective use of such a large news
video archive, we assumed that analysis of its chronological and
semantic structure becomes important. We also consider that providing
the users with the development of news topics is more important to help
their understanding of current affairs, rather than providing a list of
relevant news stories as in most of the current news video retrieval
systems. Therefore, in this paper, we propose a structuring method for a
news video archive, together with an interface that visualizes the
structure, so that users could track the development of news topics
according to their interest, efficiently. The proposed news video
structure, namely the “topic thread structure”, is obtained
as a result of an analysis of the chronological and semantic relation
between news stories. Meanwhile, the proposed interface, namely
“mediaWalker II”, allows users to track the development of
news topics along the topic thread structure, and at the same time watch
the video footage corresponding to each news story. Analyses on the
topic thread structures obtained by applying the proposed method to
actual news video footages revealed interesting and comprehensible
relations between news topics in the real world. At the same time,
analyses on their size quantified the efficiency of tracking a user's
topic-of-interest based on the proposed topic thread structure. We
consider this as a first step towards facilitating video authoring by
users based on existing contents in a large-scale news video archive.
