Video Segmentation Using Hidden Markov Model with Multimodal Features
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Bae, Tae Meon | - |
| dc.contributor.author | Jin, Sung Ho | - |
| dc.contributor.author | Ro, Yong Man | - |
| dc.date.accessioned | 2010-12-01T08:29:33Z | - |
| dc.date.available | 2010-12-01T08:29:33Z | - |
| dc.date.issued | 2004 | - |
| dc.identifier.citation | International Conference on Image and Video Retrieval 2004 | en |
| dc.identifier.uri | http://hdl.handle.net/10203/20600 | - |
| dc.description.abstract | In this paper, a video segmentation algorithm based on Hidden Markov Model classifier with multimodal feature is proposed. By using Hidden Markov Model classifier with both audio and visual features, erroneous shot boundary detection and over-segmentation were avoided compared with conventional algorithms. The experimental results show that the propose method is effective in shot detection. | en |
| dc.description.sponsorship | This research was supported in part by “SmarTV” project from Electronics and Telecommunications Research Institute. | en |
| dc.language.iso | en_US | en |
| dc.publisher | Springer Verlag | en |
| dc.title | Video Segmentation Using Hidden Markov Model with Multimodal Features | en |
| dc.type | Article | en |
- Appears in Collection
- EE-Conference Papers(학술회의논문)
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