'Gaussian pyramid' presentation slideshows

Image Pyramids and Blending

830 views • 52 slides

Dr. J. Shanbehzadeh Shanbehzadeh@gmail M.HosseinKord

571 views • 41 slides

Motion

Motion. Optical flow. Measurement of motion at every pixel. Problem definition: optical flow. Key assumptions color constancy : a point in H looks the same in I For grayscale images, this is brightness constancy small motion : points do not move very far

561 views • 37 slides

Recap from Monday

Recap from Monday. Frequency domain analytical tool computational shortcut compression tool. Fourier Transform in 2d. in Matlab, check out: imagesc(log(abs(fftshift(fft2(im)))));. Image Blending (Szeliski 9.3.4). Google Street View. CS129: Computational Photography

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Recall: Gaussian smoothing/sampling

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Image Stitching II

Image Stitching II. Ali Farhadi CSE 455 Several slides from Rick Szeliski , Steve Seitz, Derek Hoiem , and Ira Kemelmacher. RANSAC for Homography. Initial Matched Points. RANSAC for Homography. Final Matched Points. RANSAC for Homography. Image Blending. 0. 1. 0. 1. =. +.

458 views • 31 slides

Gaussian Pyramid and Its Applications

Gaussian Pyramid and Its Applications. Speaker: Po-Hung Wu. Outline. Introduction Gaussian and Laplacian pyramid Application Salient region detection Edge-aware image processing Conclusion Reference. Introduction. Why Gaussian? Easy to implement! A hierarchical way!. Introduction.

511 views • 28 slides

Object Oriented Framework for CUDA based Image Processing

Object Oriented Framework for CUDA based Image Processing. Pritam Prakash Shete , Venkat P. P. K., Dinesh M. Sarode , Mohini Laghate , S. K. Bose & R. S. Mundada , Bhabha Atomic Research Centre, Mumbai, India .

372 views • 22 slides

Algorithms and Applications in Computer Vision

Algorithms and Applications in Computer Vision. Lihi Zelnik -Manor lihi@ee.technion.ac.il Lecture 5: Pyramids. Image information occurs at all spatial scales. Image pyramids. Gaussian pyramid Laplacian pyramid. The Gaussian pyramid. Smooth with gaussians, because

348 views • 20 slides

Algorithms and Applications in Computer Vision

Algorithms and Applications in Computer Vision. Lihi Zelnik -Manor lihi@ee.technion.ac.il Lecture 5: Pyramids. Image information occurs at all spatial scales. Image pyramids. Gaussian pyramid Laplacian pyramid. The Gaussian pyramid. Smooth with gaussians, because

534 views • 20 slides

Moving Gradients: A Path-Based Method for Plausible Image Interpolation

Moving Gradients: A Path-Based Method for Plausible Image Interpolation. Alex Yin, Sayuri Soejima, Simon Yang. Moving Gradients: A Path-Based Method for Plausible Image Interpolation. Authors: Dhruv Mahajan (Columbia University) Fu-Chung Huang (UC Berkeley) Wojciech Matusik (Adobe Systems)

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Computer Vision REU Week 8 & 9

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Image Pyramids

Image Pyramids. Computer Vision, winter 2012-13 CS Department, Technion. Topics. The Gaussian Pyramid The Laplacian Pyramid Applications: Pattern Matching Coding (Compression) Enhancement Blending. Gaussian Pyramid. Gaussian Pyramid. Approximation filter is not Gaussian

1.66k views • 17 slides

Motivation

Professional. Motivation. Problem : Amateur photographers take unappealing pictures (e.g. personal and business use) Help users take better pictures with digital cameras Solution : Improve composition during image acquisition Detect main subject in the picture

111 views • 11 slides

Computer Vision REU Week 3

Computer Vision REU Week 3. Adam Kavanaugh. Lucas Kanade Method. Algorithm Overview Create Gaussian Kernels Convolute both images with dx and dy Gaussian Kernel Take the average of the resulting convolutions between both images in x and y direction

238 views • 10 slides