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Freeman Algorithms and Applications in Computer Vision Lihi Zelnik-Manor Lecture 5: Pyramids.

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Presentation on theme: "Freeman Algorithms and Applications in Computer Vision Lihi Zelnik-Manor Lecture 5: Pyramids."— Presentation transcript:

1 Freeman Algorithms and Applications in Computer Vision Lihi Zelnik-Manor lihi@ee.technion.ac.il Lecture 5: Pyramids

2 Freeman Image information occurs at all spatial scales

3 Freeman Image pyramids

4 Freeman The Gaussian pyramid Smooth with gaussians, because – a gaussian*gaussian=another gaussian Gaussians are low pass filters, so representation is redundant.

5 Freeman The computational advantage of pyramids http://www-bcs.mit.edu/people/adelson/pub_pdfs/pyramid83.pdf

6 Freeman http://www-bcs.mit.edu/people/adelson/pub_pdfs/pyramid83.pdf

7 Freeman

8 Gaussian pyramids used for up- or down- sampling images. Multi-resolution image analysis – Look for an object over various spatial scales – Coarse-to-fine image processing: form blur estimate or the motion analysis on very low- resolution image, upsample and repeat. Often a successful strategy for avoiding local minima in complicated estimation tasks.

9 Freeman Image pyramids

10 Freeman The Laplacian Pyramid Synthesis – Compute the difference between upsampled Gaussian pyramid level and Gaussian pyramid level. – band pass filter - each level represents spatial frequencies (largely) unrepresented at other level.

11 Freeman Laplacian pyramid algorithm

12 Freeman Showing, at full resolution, the information captured at each level of a Gaussian (top) and Laplacian (bottom) pyramid. http://www-bcs.mit.edu/people/adelson/pub_pdfs/pyramid83.pdf

13 Freeman Gaussian pyramid

14 Freeman Laplacian pyramid

15 Freeman Why use these representations? Handle real-world size variations with a constant-size vision algorithm. Remove noise Analyze texture Recognize objects Label image features

16 Freeman http://web.mit.edu/persci/people/adelson/pub_pdfs/RCA84.pdf

17 Freeman http://www.hackerfactor.com/blog/index.php?/archives/440-The-Perfect-Blend.html

18 Freeman http://www.hackerfactor.com/blog/index.php?/archives/440-The-Perfect-Blend.html

19 Freeman Slide Credits Trevor Darrell Bill Freeman and others, as noted…

20 Freeman More on statistics of natural scenes Olshausen and Field: – Natural Image Statistics and Efficient Coding, https://redwood.berkeley.edu/bruno/papers/stirling.ps.Z https://redwood.berkeley.edu/bruno/papers/stirling.ps.Z – Relations between the statistics of natural images and the response properties of cortical cells. – http://redwood.psych.cornell.edu/papers/field_87.pdf http://redwood.psych.cornell.edu/papers/field_87.pdf Aude Olivia: – http://cvcl.mit.edu/SUNSlides/9.912-CVC-ImageAnalysis- web.pdf http://cvcl.mit.edu/SUNSlides/9.912-CVC-ImageAnalysis- web.pdf


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