'Bundle adjustment' presentation slideshows

Motion from image and inertial measurements

Motion from image and inertial measurements. Dennis Strelow Carnegie Mellon University. On the web. Related materials: these slides related papers movies VRML models at: http://www.cs.cmu.edu/~dstrelow/northrop2005. Introduction (1). From an image sequence, we can recover:

1.28k views • 114 slides

Image stitching

Image stitching. Digital Visual Effects Yung-Yu Chuang. with slides by Richard Szeliski, Steve Seitz, Matthew Brown and Vaclav Hlavac. Image stitching. Stitching = alignment + blending. geometrical registration. photometric registration. Applications of image stitching.

1.25k views • 84 slides

Image Stitching

1.28k views • 79 slides

Computational Photography Image-based Modeling (Cont.)

Computational Photography Image-based Modeling (Cont.). Jinxiang Chai. Image-based Modeling and Rendering. Model. Panoroma. Image-based rendering. Image based modeling. Images + Depth. Geometry+ Images. Camera + geometry. Images user input range scans. Images. Geometry+ Materials.

779 views • 60 slides

CSCE 641 Computer Graphics: Image-based Modeling (Cont.)

CSCE 641 Computer Graphics: Image-based Modeling (Cont.). Jinxiang Chai. Image-based Modeling and Rendering. Model. Panoroma. Image-based rendering. Image based modeling. Images + Depth. Geometry+ Images. Camera + geometry. Images user input range scans. Images . Geometry+ Materials.

884 views • 59 slides

Photo Stitching Panoramas from Multiple Images

02/28/12. Photo Stitching Panoramas from Multiple Images. Computer Vision CS 543 / ECE 549 University of Illinois Derek Hoiem. Homeworks. HW 2 due today Will try to have it graded by Mar 8 (ECCV deadline on March 5) HW 3 has been released (due in 2 weeks) Who designs/grades?

744 views • 49 slides

Structure from motion

Structure from motion. Structure from motion. Given a set of corresponding points in two or more images, compute the camera parameters and the 3D point coordinates. ?. ?. Camera 1. ?. Camera 3. ?. Camera 2. R 1 ,t 1. R 3 ,t 3. R 2 ,t 2. Slide credit: Noah Snavely. X j. x 1 j.

926 views • 49 slides

Stanford CS223B Computer Vision, Winter 2007 Lecture 8 Structure From Motion

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Structure from motion Class 9

709 views • 47 slides

Simple Calibration of Non-overlapping Cameras with a Mirror

Simple Calibration of Non-overlapping Cameras with a Mirror. Ram Krishan Kumar 1 , Adrian Ilie 1 , Jan-Michael Frahm 1 , Marc Pollefeys 1,2 Department of Computer Science 1 UNC Chapel Hill 2 ETH Zurich USA Switzerland. &. CVPR, Alaska, June 2008.

549 views • 45 slides

Stanford CS223B Computer Vision, Winter 2006 Lecture 8 Structure From Motion

Stanford CS223B Computer Vision, Winter 2006 Lecture 8 Structure From Motion. Professor Sebastian Thrun CAs: Dan Maynes-Aminzade, Mitul Saha, Greg Corrado Slides by: Gary Bradski, Intel Research and Stanford SAIL. Structure From Motion. features. camera.

781 views • 44 slides

CSCE 641 Computer Graphics: Image-based Modeling (Cont.)

CSCE 641 Computer Graphics: Image-based Modeling (Cont.). Jinxiang Chai. Image-based Modeling and Rendering. Model. Panoroma. Image-based rendering. Image based modeling. Images + Depth. Geometry+ Images. Camera + geometry. Images user input range scans. Images. Geometry+ Materials.

654 views • 42 slides

Panorama Stitching and Augmented Reality

Panorama Stitching and Augmented Reality. Local feature matching with large datasets. Examples: Identify all panoramas and objects in an image set Identify all products in a supermarket Identify any location for robot localization or augmented reality. Matching in large unordered datasets.

523 views • 31 slides

Projective 2D geometry course 2

Projective 2D geometry course 2. Multiple View Geometry Comp 290-089 Marc Pollefeys. Content. Background : Projective geometry (2D, 3D), Parameter estimation, Algorithm evaluation. Single View : Camera model, Calibration, Single View Geometry.

519 views • 28 slides

An extreme occurrence of the missing data

416 views • 27 slides

3D Photorealistic Modeling Process

3D Photorealistic Modeling Process. Different Sensors. Scanners Local coordinate system Cameras Local camera coordinate system GPS Global coordinate system. Coordinate Systems. Individual local scanner coordinates (each scan)

350 views • 24 slides

Digital Imaging and Remote Sensing Laboratory

Automatic Tie-Point and Wire-frame Generation From Oblique Aerial Imagery. Seth Weith-Glushko Advisor: Carl Salvaggio Research Proposal November 7, 2003. Digital Imaging and Remote Sensing Laboratory. Table of Contents. The Problem Specific Aims Proposed Solution

366 views • 24 slides

SLAM (Simultaneously Localization and Mapping)

SLAM (Simultaneously Localization and Mapping). Presenter : Jeongkyun Lee. Contents. What is SLAM SfM -based SLAM Filter-based SLAM Comparison Other SLAMs Research topics. What is SLAM. Simultaneously Localization and Mapping. Unknown Environment. Given only images. Unknown Pose.

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SIFT Demo

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179 views • 3 slides