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Video scene analysis in 3D wavelet transform domain

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Abstract

This paper proposes a novel scene analysis algorithm based on three-dimensional discrete wavelet transform (3D DWT). Based on the correlation among the adjacent frames, video frames can be considered as four categories: abrupt scene transition, motion scene, gradual scene transition and static scene, which are ranked from low to high according to the strength of the correlation. Through the investigation of the particular temporal and spatial distribution of each category, the correlation among adjacent frames could be described by the 3D DWT coefficients related statistical features, which are the energy of high-frequency coefficients difference, the sum of high-frequency coefficients magnitudes and the difference of low-frequency coefficients magnitudes. The energy of high-frequency coefficients difference is first used to detect the abrupt scene transition including cut and flashlight. Then all the three features are input to SVM for the purpose of analyzing the residual scenes and detecting the gradual scene transition, such as dissolve and fade. Experimental results show the method to be effective not only for the abrupt scene transition detection, but also for the gradual scene transition detection.

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Acknowledgements

This work is supported in part by the National 973 Project (No.2007CB311002), National 863 Project (No.2009AA01Z409), and National Natural Science Foundation of China Project (NSFC, No.60903121).

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  1. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Zhi Li & Guizhong Liu

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  1. Zhi Li
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  2. Guizhong Liu
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Correspondence to Guizhong Liu.

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Li, Z., Liu, G. Video scene analysis in 3D wavelet transform domain. Multimed Tools Appl 56, 419–437 (2012). https://doi.org/10.1007/s11042-010-0594-z

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