Computer Vison at ETHZ - ETH Zurich

Flashcards and summaries for Computer Vison at the ETHZ - ETH Zurich

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Study with flashcards and summaries for the course Computer Vison at the ETHZ - ETH Zurich

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What is stereo geometry?

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What are features in an image that convey depth information?

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Whats disparity?

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Exemplary flashcards for Computer Vison at the ETHZ - ETH Zurich on StudySmarter:

What's the baseline in Epipolar Geometry?

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Why is the epipolar constraint useful?

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Beyond the hard constraint of epipolar geometry what are  "soft" constraints to help identify corresponding points?

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How do you find correspondences with the similarity constraint?

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Exemplary flashcards for Computer Vison at the ETHZ - ETH Zurich on StudySmarter:

What are the extrinsic parameters of camera calibration?

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What are the intrinsic parameters of camera calibration?

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What is a rigid body?

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How many degrees of freedom does a rigid body transformation have in 3D?

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Exemplary flashcards for Computer Vison at the ETHZ - ETH Zurich on StudySmarter:

What is the vanishing point?

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Exemplary flashcards for Computer Vison at the ETHZ - ETH Zurich on StudySmarter:

Computer Vison

What is stereo geometry?

It is that we have multiple views of the same thing

Computer Vison

What are features in an image that convey depth information?

shadows, texture, focus/blurs, parallel/converging lines, lighting shading, occlusion, size/scale

Computer Vison

Whats disparity?

The disparity is the distance a point has moved with respect to another picture.

Computer Vison

What's the baseline in Epipolar Geometry?

It's the line joining the camera centers.

Computer Vison

Why is the epipolar constraint useful?

Because it reduces the correspondence problem (finding two corresponding pixels) to a 1D search along an epipolar line.

Computer Vison

Beyond the hard constraint of epipolar geometry what are  "soft" constraints to help identify corresponding points?

  1. Similarity (points look similar)
  2. Uniqueness (no more than one match)
  3. Ordering (same ordering of points in the images)
  4. Disparity gradient is limited (depth doesn't change too quickly)

Computer Vison

How do you find correspondences with the similarity constraint?

With an image patch, you iterate over the image and calculate their SSD (sum of squared differences) and where there is a global minimum is where the match is.

Computer Vison

What are the extrinsic parameters of camera calibration?

Its where the camera 3D coordinate system is with respect to the world coordinate system.

Computer Vison

What are the intrinsic parameters of camera calibration?

It's the parameters that define the projection from the 3D coordinates in the camera coordinate system to the 2D image plane.

Computer Vison

What is a rigid body?

It's a collection of points whose relative position can't change.

Computer Vison

How many degrees of freedom does a rigid body transformation have in 3D?

6 because 3 are for fixing the position of one point and 3 are for rotating around each axis.

Computer Vison

What is the vanishing point?

Its where parallel lines meet in a picture.

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