adaptive image and video retargeting technique based on fourier analysis jun-seong kim, jin-hwan...

Adaptive Image and Video Retargeting Technique Based on Fourier Analysis

Jun-Seong Kim, Jin-Hwan Kim, and Chang-Su KimSchool of Electrical Engineering, Korea University, Seoul, Korea

Reporter: Chia-Hao HsiehDate: 20100316

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Outline

• Introduction• Methods• Simulation results

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Introduction

Original Scaled Cropped Retargeted

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Introduction

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Methods

• Partitioning• Scaling distortions• Adaptive scaling

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Partitioning

K = 10 in this work

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Scaling distortions

• z[n]: a row signal of length lk in the kth strip

• Reduce the length by removing rk pixels to obtain a downsampled signal zd[n]

• The sampling rate is reduced by a factor of (1-(rk/lk))π

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Scaling distortions

• The signal should be lowpass-filtered with a cutoff frequency ωc = (1-(rk/lk))π to avoid aliasing artifacts

• Scaling distortions (The energy of the lost high frequency components)

Can be approximated by

Except for the dominant DC component

A smaller sk makes the exponential function decrease more quickly

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Scaling distortions

Can be approximated by

Scaling distortion of the kth strip:

Except for the dominant DC component

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Adaptive scaling

To minimize the sum of the distortions of strips

R = Ws − Wt

Constrained optimization problemCan be solved by minimizing the Lagrangian cost function

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Adaptive scaling

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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.

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Simulation Results

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Simulation Results

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Conclusions

• The proposed algorithm requires much less computations than the seam carving

• Excellent temporal coherence without jitter artifacts