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