Image Matching Methods Quiz

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How is sparse image matching different from dense image matching?

Sparse image matching produces a 3D point cloud, while dense image matching computes epipolar lines.

Sparse image matching produces matches for every pixel, while dense image matching produces matches for specific points.

Sparse image matching operates on B&W images, while dense image matching uses color images.

Sparse image matching computes high-quality matches for specific points, while dense image matching computes lower-quality matches for every pixel. (correct)

In the context of image matching, what method involves operating on black and white images to detect interest points?

Least-squares matching

Epipolar resampling

Harris operator (correct)

Cross-correlation

What is the purpose of traditional relative orientation in the context of image processing?

To pre-calibrate cameras for image capturing.

To produce a dense 3D point cloud.

To compute high-quality matches for each pixel.

To determine the RO parameters for computing epipolar lines. (correct)

What technique is used to identify incorrect matches during feature point matching?

Harris operator Signup and view all the answers

Which method is employed to produce a set of high-quality matches for stereo pairs in image processing?

Sparse image matching Signup and view all the answers

What role does autonomous relative orientation play in feature point matching?

Determining interest points in images. Signup and view all the answers

What is an interest point in the context of autonomous relative orientation?

A point distinct from its surroundings Signup and view all the answers

How is the search space reduced in autonomous relative orientation using the epipolar line constraint?

By turning it into a 2D search Signup and view all the answers

What does the elevation range constraint achieve in reducing the search space in relative orientation?

Approximates the feature height Signup and view all the answers

How does the use of an image pyramid reduce the search space in relative orientation?

By reducing image resolution in a pyramid structure Signup and view all the answers

In relative orientation, what is the purpose of area-based matching?

To determine feature matching based on brightness values Signup and view all the answers

How does traditional relative orientation differ from autonomous relative orientation?

Traditional RO requires manual intervention while autonomous RO is automated Signup and view all the answers

What is the main reason it is not possible to solve for all 12 parameters in a stereo pair?

Limited geometric degrees of freedom Signup and view all the answers

In the context of dependent relative orientation, what condition must be satisfied for all vectors to be in the same coordinate system?

Orthogonality Signup and view all the answers

What is a benefit of having a 60% overlap in feature matching for autonomous relative orientation?

Improved matching accuracy Signup and view all the answers

Which parameter is typically held constant in traditional relative orientation when selecting and measuring points?

Camera focal length Signup and view all the answers

What distinguishes autonomous relative orientation from traditional relative orientation in terms of point selection?

Automatic feature extraction Signup and view all the answers

In feature matching, what does high redundancy among points imply?

Greater robustness to outliers Signup and view all the answers

What impact does a low feature matching accuracy have on autonomous relative orientation?

Reduced effectiveness of triangulation Signup and view all the answers

Image Matching Methods Quiz

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