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Autoregressive video modeling through 2D Wavelet Statistics

Omidyeganeh, M ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1109/IIHMSP.2010.75
  3. Publisher: 2010
  4. Abstract:
  5. We present an Autoregressive (AR) modeling method for video signal analysis based on 2D Wavelet Statistics. The video signal is assumed to be a combination of spatial feature time series that are temporally approximated by the AR model. The AR model yields a linear approximation to the temporal evolution of a stationary stochastic process. Generalized Gaussian Density (GGD) parameters, extracted from 2D wavelet transform subbands, are used as the spatial features. Wavelet transform efficiently resembles the Human Visual System (HVS) characteristics and captures more suitable features, as compared to color histogram features. The AR model describes each spatial feature vector as a linear combination of the previous vectors within a reasonable time interval. Shot boundaries are well detected based on the AR prediction errors, and then at least one keyframe is extracted from each shot. Experimental results confirm high accuracy of the proposed method compared to existing methods, such as [5]
  6. Keywords:
  7. Keyframe selection ; Video scene analysis ; 2-D wavelet transform ; 2D Wavelet ; 2D wavelet marginal statistics ; AR models ; Auto-regressive ; Autoregressive modeling ; Color histogram ; Existing method ; Generalized Gaussian density ; Human visual systems ; Key frame selection ; Key frames ; Linear approximations ; Linear combinations ; Prediction errors ; Shot boundary ; Spatial feature vector ; Spatial features ; Stationary stochastic process ; Sub-bands ; Temporal evolution ; Time interval ; Video modeling ; Video scene ; Video signal ; Argon ; Image retrieval ; Mathematical transformations ; Multimedia signal processing ; Random processes ; Signal processing ; Stochastic models ; Time series ; Wavelet transforms
  8. Source: Proceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010, 15 October 2010 through 17 October 2010 ; October , 2010 , Pages 272-275 ; 9780769542225 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/5638028