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MIR
2006
ACM

Robust scene recognition using language models for scene contexts

14 years 5 months ago
Robust scene recognition using language models for scene contexts
We propose a robust scene recognition framework using scene context information for multimedia contents. Multimedia contents consist of scene sequences that are more likely to happen compared with other scene sequences. We employ a statistical approach to deal with this scene context information. We employ a hidden Markov model (HMM) to model each scene and n-gram language model to represent the contexts among scenes. We evaluated the proposed method in scene recognition experiments for 16 scenes in video data of 25 baseball games. The proposed method significantly improved the results compared to that without scene context information. Categories and Subject Descriptors I.2.10 [Vision and Scene Understanding]: Video analysis; I.4.8 [Scene Analysis]: Time-varying imagery General Terms Algorithms, Experimentation Keywords CBVIR, sports video, indexing, HMM, n-gram model
Ryoichi Ando, Koichi Shinoda, Sadaoki Furui, Takah
Added 14 Jun 2010
Updated 14 Jun 2010
Type Conference
Year 2006
Where MIR
Authors Ryoichi Ando, Koichi Shinoda, Sadaoki Furui, Takahiro Mochizuki
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