ICTACT Journal on Image and Video Processing

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Shot Boundary Detection Using Hilbert Transform Based Features


Affiliations
1 School of Information Technology and Engineering, Vellore Institute of Technology, India
2 Department of Computer Applications, National Institute of Technology-Tiruchirappalli, India
     

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The first and foremost step in the shot boundary detection is the extraction of features from the video sequences. To obtain better performance in shot boundary detection, a new method is proposed in this paper, where texture and local binary information extracted from the hilbert transformed frames are processed and represented as features. The similarity between the frames is constructed as continuity signal. The boundaries between the shots are identified by applying the shot transition identification procedure on the continuity signals. The proposed method is evaluated over the TRECVID 2007 SBD dataset and the performance is compared to the top performers of TRECVID 2007 SBD task.

Keywords

Shot Boundary Detection, Hilbert Transform, Local Binary Information, Texture Feature, Shot Change Transition Identification.
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  • Shot Boundary Detection Using Hilbert Transform Based Features

Abstract Views: 246  |  PDF Views: 0

Authors

G. G. Lakshmi Priya
School of Information Technology and Engineering, Vellore Institute of Technology, India
S. Domnic
Department of Computer Applications, National Institute of Technology-Tiruchirappalli, India

Abstract


The first and foremost step in the shot boundary detection is the extraction of features from the video sequences. To obtain better performance in shot boundary detection, a new method is proposed in this paper, where texture and local binary information extracted from the hilbert transformed frames are processed and represented as features. The similarity between the frames is constructed as continuity signal. The boundaries between the shots are identified by applying the shot transition identification procedure on the continuity signals. The proposed method is evaluated over the TRECVID 2007 SBD dataset and the performance is compared to the top performers of TRECVID 2007 SBD task.

Keywords


Shot Boundary Detection, Hilbert Transform, Local Binary Information, Texture Feature, Shot Change Transition Identification.