Smoothly Varying Affine Stitching [CVPR 2011] Ph.D. Student, Chang-Ryeol Lee February 10, 2013

Contents Introduction Related works Proposed method Expeirments Motivation Problem Related works Dynamosaics: Video Mosaics with Non-Chronological Time [CVPR 2005] Proposed method Smoothly Varying Affine Stitching [CVPR 2011] Expeirments

Introduction Motivation Typical camera FOV: 50˚ X 35˚

Introduction Motivation Typical camera FOV: 50˚ X 35˚ Human FOV: 200˚ X 135˚

Introduction Motivation Typical camera FOV: 50˚ X 35˚ Human FOV: 200˚ X 135˚ Panoramic view: 360˚ X 180˚

Introduction Impressive

Introduction Problem Usually generating using rotating the camera around the center of projection: The mosaic has a natural interpretation in 3D The images are reprojected onto a common plane The mosaic is formed on this plane

Introduction Problem: Changing Camera Center synthetic PP PP1 PP2

Introduction Problem: Changing Camera Center Pics from Internet

Related works Dynamosaics: Video Mosaics with Non-Chronological Time [CVPR 2005] Shmuel Peleg (Hebrew University, Israel) Motivation Satellites create panoramas by scanning 1D sensor Rotation & Translation How can this idea be utilized?

Related works Push broom stitching t t+1 t+2

Related works Time-Space Cube Align the images Create Push-broom mosaics by combining the image pieces Different Cuts can create different mosaics 1 2 3 4 5

Related works Push broom distortion Experimental result x-axis: Orthographic Projection y-axis: Perspective Projection y shrinks as Z increases, x doesn’t Experimental result

Proposed method Smoothly Varying Affine Stitching [CVPR 2011] Loong-Fah Cheong (NUS) Work Assumption Most scenes can be modeled as having smoothly varying depth A global affine has general shape preservation

Proposed method System overview

Proposed method The affine stitching field

Proposed method Algorithm to compute stitching field Input: Output: M Base image features N Target image features Global affine matrix Output: Converged affine matrix

Proposed method Algorithm to compute stitching field Cost function Notation Affine parameters Stitched feature points by

Proposed method Algorithm to compute stitching field Cost function Notation Robust Gaussian mixture Smoothness regularization : Fourier transform of : Fourier transform of Gaussian

Proposed method Algorithm to compute stitching field Cost function Minimization by EM style optimization Estimated stitching field map

Applications Re-shoot

Applications Re-shoot

Experiments Panoramic stitching

Experiments Matching

Thank you! * This material is based on Raz Nossek‘s Image Registration & Mosaicing.