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Adaptive Image and Video Retargeting Technique Based on Fourier Analysis Jun-Seong Kim, Jin-Hwan Kim, and Chang-Su Kim School of Electrical Engineering, Korea University, Seoul, Korea Reporter: Chia-Hao Hsieh Date:

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Outline Introduction Methods Simulation results 2

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Introduction OriginalScaledCroppedRetargeted 3

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Introduction 4

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Methods Partitioning Scaling distortions Adaptive scaling 5

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Partitioning K = 10 in this work 6

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Scaling distortions z[n]: a row signal of length l k in the kth strip Reduce the length by removing r k pixels to obtain a downsampled signal z d [n] The sampling rate is reduced by a factor of (1- (r k /l k ))π 7

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Scaling distortions The signal should be lowpass- ltered with a cutoff frequency ω c = (1-(r k /l k ))π to avoid aliasing artifacts Scaling distortions (The energy of the lost high frequency components) Can be approximated by 8 Except for the dominant DC component A smaller s k makes the exponential function decrease more quickly

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Scaling distortions Can be approximated by Scaling distortion of the kth strip: 9 Except for the dominant DC component

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Adaptive scaling To minimize the sum of the distortions of strips R = W s W t Constrained optimization problem Can be solved by minimizing the Lagrangian cost function 10

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Adaptive scaling 11

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Extension to video retargeting Cut the volume into parallelepipeds along the time axis Each parallelpiped is scaled down spatially Partitioning of a video sequence for horizontal resizing. 12

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Simulation Results 13

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Simulation Results 14

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Conclusions The proposed algorithm requires much less computations than the seam carving Excellent temporal coherence without jitter artifacts 15

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