Video Story Segmentation and Its Application to Personal Video Recorders

Hoashi, Keiichiro; Sugano, Masaru; Naito, Masaki; Matsumoto, Kazunori; Sugaya, Fumiaki

doi:10.1007/11526346_6

Cited by 2 publications

(4 citation statements)

References 5 publications

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“…We have shown that this is possible and investigated which parameters give the best results. The future direction of our work will be to investigate how the system can be further improved, and to incorporate the story segmentation methods presented in [5] in order to achieve an even more autonomous system.…”

Section: Discussionmentioning

confidence: 99%

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Adaptive Video News Story Tracking based on Earth Mover'S Distance

Uddenfeldt

Hoashi

Matsumoto

et al. 2006

2006 IEEE International Conference on Multimedia and Expo

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This paper proposes an adaptive system for video news story tracking based on the Earth Mover's Distance (EMD). When an interesting story appears in the news, it is flagged manually as a topic for tracking. Our system then tracks the events as they unfold over time and present accumulated results to the user for feedback. This feedback is used to adapt the topic model to changes in the tracked story. EMD provides the system with a robust way of performing many-to-many matching of news stories independent of the temporal order of their contents. This is particularly suitable in the news genre as stories often are subjected to video editing between shows. Experiments have been run with a range of topics and show promising results.

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Section: Discussionmentioning

confidence: 99%

“…We will assume that the news feed has already been segmented into shots and stories. This segmentation can be achieved using many different techniques [4,5], neither of which is favored by our system.…”

Section: Proposed Tracking Systemmentioning

confidence: 99%

Adaptive Video News Story Tracking based on Earth Mover'S Distance

Uddenfeldt

Hoashi

Matsumoto

et al. 2006

2006 IEEE International Conference on Multimedia and Expo

Self Cite

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“…Novel methods are e.g. based on SVMs [3]. A standardised evaluation of the different shot boundary detection methods is TRECVID [1].…”

Section: Video Layers and Their Boundary Detectionmentioning

confidence: 99%

“…The latter is of course preferable, as it avoids cost-intensive and error-prone manual work. Yet, it involves various challenging research topics, like automatic indexing [1,2,3], person identification [4,5,6], speech recognition [7], understanding [8], and summarisation [9]. In this work we address the first step towards the automatic analysis: finding shot and scene boundaries in videos.…”

Section: Introductionmentioning

confidence: 99%

A Two-Layer Graphical Model for Combined Video Shot and Scene Boundary Detection

Al-Hames

Zettl

Wallhoff

et al. 2006

2006 IEEE International Conference on Multimedia and Expo

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In this work we present a novel two-layer hybrid Graphical model for combined shot and scene boundary detection in videos. In the first layer of the model, low-level features are used to detect shot boundaries. The shot layer is connected to a higher layer that detects scene or chapter boundaries from semantic features. With this structure, the model optimises the alignment for both layers at the same time and the detection results are interconnected. Experimental results on real video data show, that both layers highly benefit from this sharing of information. Compared to a baseline threshold method with the same features, the F-measure result for the shot detection has been improved by 12.6% absolute. For the scene boundary detection, the result has been improved by more than 11% absolute.

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Video Story Segmentation and Its Application to Personal Video Recorders

Cited by 2 publications

References 5 publications

Adaptive Video News Story Tracking based on Earth Mover'S Distance

Adaptive Video News Story Tracking based on Earth Mover'S Distance

A Two-Layer Graphical Model for Combined Video Shot and Scene Boundary Detection

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