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Communication Dans Un Congrès Année : 2011

Automatic Multilevel Temporal Video Structuring

Résumé

In this paper we propose a novel and complete video scene segmentation framework, developed on different structural levels of analysis. Firstly, a shot boundary detection algorithm is introduced that extends the graph partition method with a nonlinear scale space filtering technique which increase the detection efficiency with gains of 7,4% to 9,8% in terms of both precision and recall rates. Secondly, static storyboards are formed based on a leap keyframe extraction method that selects a variable number of keyframes, adapted to the visual content variation, for each detected shot. Finally using the tracted keyframes, spatio-temporal coherent shots are clustered into the same scene based on temporal constraints and with the help of a new concept of neutralized shots. Video scenes are obtained with average precision and recall rates of 86%.
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Dates et versions

hal-00735694 , version 1 (26-09-2012)

Identifiants

  • HAL Id : hal-00735694 , version 1

Citer

Ruxandra Tapu, Titus Zaharia. Automatic Multilevel Temporal Video Structuring. 2011 IEEE Fifth International Conference on Semantic Computing, Sep 2011, Palo Alto, California, United States. pp.387-394. ⟨hal-00735694⟩
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