A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic partitioning of full-motion video
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Proceedings of the third ACM international conference on Multimedia
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Video Segmentation Using Color Difference Histogram
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A feature-based algorithm for detecting and classifying production effects
Multimedia Systems
A fast algorithm for video parsing using MPEG compressed sequences
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International Journal of Intelligent Systems
Efficient MPEG compressed video analysis using macroblock typeinformation
IEEE Transactions on Multimedia
Effective wipe detection in MPEG compressed video using macro block type information
IEEE Transactions on Multimedia
Temporal segmentation of video using frame and histogram space
IEEE Transactions on Multimedia
Rapid scene analysis on compressed video
IEEE Transactions on Circuits and Systems for Video Technology
A unified approach to shot change detection and camera motion characterization
IEEE Transactions on Circuits and Systems for Video Technology
Performance characterization of video-shot-change detection methods
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Effective Fades and Flashlight Detection Based on Accumulating Histogram Difference
IEEE Transactions on Circuits and Systems for Video Technology
A Formal Study of Shot Boundary Detection
IEEE Transactions on Circuits and Systems for Video Technology
Application of 3D-wavelet statistics to video analysis
Multimedia Tools and Applications
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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.