'Intrinsic parameters' diaporamas de présentation

Lecture 2, Pinhole Camera Model

Lecture 2, Pinhole Camera Model. Last time we talked through the pinhole projection. This time we are going to look at the coordinate systems in the pinhole camera model. Some context. O ur goal is to understand the process of stereo vision, which requires understanding:

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3D Vision

3D Vision. CSc I6716 Spring 2011. Topic 3 of Part II Stereo Vision. Zhigang Zhu, City College of New York zhu@cs.ccny.cuny.edu. Stereo Vision. Problem Infer 3D structure of a scene from two or more images taken from different viewpoints Two primary Sub-problems

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CS143, Brown James Hays

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2nd Joined Advanced Student School

2nd Joined Advanced Student School. Calibration Benjamin Fingerle Christian Wachinger. A Definition of Calibration.

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3D Sensing

3D Sensing. 3D Shape from X Perspective Geometry Camera Model Camera Calibration General Stereo Triangulation 3D Reconstruction. 3D Shape from X. shading silhouette texture stereo light striping motion. mainly research. used in practice. Perspective Imaging Model: 1D.

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Calibration

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A Flexible New Technique for Camera Calibration Zhengyou Zhang

A Flexible New Technique for Camera Calibration Zhengyou Zhang. Sung Huh CSPS 643 Individual Presentation 1 February 25, 2009. Outline. Introduction Equations and Constraints Calibration and Procedure Experimental Results Conclusion. Outline. Introduction Equations and Constraints

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Introduction to 3D Vision

Introduction to 3D Vision. How do we obtain 3D image data? What can we do with it?. What can you determine about 1. the sizes of objects 2. the distances of objects from the camera?. What knowledge do you use to analyze this image?. What objects are shown in this image?

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EECS 274 Computer Vision

EECS 274 Computer Vision. Geometric Camera Models. Geometric Camera Models. Elements of Euclidean geometry Intrinsic camera parameters Extrinsic camera parameters General form of perspective projection Reading: Chapter 1 of FP, Chapter 2 of S. Geometric camera calibration.

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Single-view geometry

Single-view geometry. Odilon Redon, Cyclops, 1914. Geometric vision. Goal: Recovery of 3D structure What cues in the image allow us to do this?. Visual cues. Shading. Merle Norman Cosmetics, Los Angeles. Slide credit: S. Seitz. Visual cues. Focus. From The Art of Photography , Canon.

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Stereopsis

Stereopsis. Reconstruction. Only need to match features across epipolar lines. Geometric Reconstruction. Pinhole Camera Model. Basic Stereo Derivations. Derive expression for Z as a function of x 1 , x 2 , f and B. Basic Stereo Derivations. Basic Stereo Derivations.

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Uncalibrated Epipolar - Calibration

Uncalibrated Epipolar - Calibration. Jana Kosecka CS223b. calibrated coordinates. Linear transformation. pixel coordinates. Uncalibrated Camera. Overview. Calibration with a rig Uncalibrated epipolar geometry. Calibrated camera. Image plane coordinates

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Camera Calibration

Camera Calibration. Camera Calibration. Issues: what are intrinsic parameters of the camera? what is the camera matrix? (intrinsic+extrinsic) General strategy: view calibration object identify image points obtain camera matrix by minimizing error

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Camera Calibration

Camera Calibration. Camera Calibration. Issues: what are intrinsic parameters of the camera? what is the camera matrix? (intrinsic+extrinsic) General strategy: view calibration object identify image points obtain camera matrix by minimizing error

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An Onboard Virtual Rumble-Strip Based Operation for Road Departure Warning

An Onboard Virtual Rumble-Strip Based Operation for Road Departure Warning. During of Project: 18 months July 1, 2010- December 31, 2011 Progress Update presented at the NATSRL Research Advisory Panel Meeting By Jiann-Shiou Yang Department of Electrical and Computer Engineering

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Geometric and Radiometric Camera Calibration

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Endoscope Exploration on Knee Surface

Endoscope Exploration on Knee Surface. 15-862 Computed Photography Final Project Chenyu Wu. Motivation. Endoscope is widely used in minimally invasive surgery. Problem. The size and distortion of endoscope images limit its use. Our Goal.

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Mariolino De Cecco , Nicolo Biasi , Ilya Afanasyev

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Optimizing LISA for cost and science

Optimizing LISA for cost and science. Sean T. McWilliams stmcwill@princeton.edu Princeton University LISA 9 Symposium, Paris, France May 24, 2012. Overview. Sensitivities and rates of NGO/SGO, Omega, and GADFLI for MBHBs, EMRIs, and GBs

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