Quiz 6
Feature Detection Quiz
Test your knowledge on feature detection and image processing techniques with our engaging quiz. Designed for enthusiasts and professionals alike, this quiz covers essential concepts like feature detection, keypoint matching, and the RANSAC algorithm.
Key Features:
- 12 challenging questions
- Multiple choice and checkbox formats
- Immediate feedback on your answers
Select all that are involved in feature detection:
Generate a description for each detected point of interest
Detection of points of interest
Find homography
What is the minimum number of point correspondences needed to determine an homography?
1
2
3
4
Select all that are, usually, involved in creating image panoramas:
Detection of keypoints (i.e. Interest points)
Matching of keypoints using the respective descriptors
Calculating an homography from the matched keypoints
Description of detected keypoints
What is true regarding the Harris corner detector:
It's invariant to scaling
It's invariant to rotation
Its most used component is the keypoint descriptor, not the detector
It's patented
Which are characteristics of a good feature?
Looks pretty
Possesses distinctive properties
Detectable under geometric and intensity changes
Uses a large quantity of information around it
What is true regarding the SIFT feature detector:
Its most used component is the keypoint descriptor, not the keypint detector
It's invariant to rotation
It's patented
It's invariant to scaling
What is true regarding the SIFT feature detector:
Its most used component is the keypoint descriptor, not the keypint detector
It's invariant to rotation
It's patented
It's invariant to scaling
Regarding the "cornerness" measure produced by the Harris corner detector, which indicates that there is NO corner:
R < 0 and |R| is large
R < 0 and |R| is small
R > 0 and |R| is large
R > 0 and |R| is small
What is the "characteristic scale"?
It's a characteristic that all keypoint detectors have
It's the scale at which the "normalized" LoG operator produces the highest peak response when convolved with another signal of approximately the same width
It's the result of applying a descriptor to a keypoint
It's the scale at which the "normalized" LoG operator produces the lowest peak response when convolved with another signal of approximately the same widt
What is the dimension of the homography matrix? Use the character x to indicate multiplication. For example, if it was 10 rows by 20 columns, you'd write 10x20, without spaces.
3x3
5x5
2x2
8x8
RANSAC will attempt several random combinations of point matches in order to select the combination that produces the best model. In each attempt, what is the number of matches is uses?
The minimum number of matches required by the assumed model. For example, stitching 2 images taken by the same camera, slightly rotated about it's optical axis, is modelled by an homography. Therefore, RANSAC will use 4 point correspondences in each attempt.
Less than the number of matches required by the assumed model. For example, stitching 2 images taken by the same camera, slightly rotated about it's optical axis, is modelled by an homography. Therefore, RANSAC will use 2 point correspondences for each attempt.
One more match than the number required by the assumed model. For example, stitching 2 images taken by the same camera, slightly rotated about it's optical axis, is modelled by an homography. Therefore, RANSAC will use 9 point correspondences for each attempt.
The maximum number of matches required by the assumed model. For example, stitching 2 images taken by the same camera, slightly rotated about it's optical axis, is modelled by an homography. Therefore, RANSAC will use 8 point correspondences in each attempt.
What is the threshold in the context of RANSAC?
It's the minimum distance a point that doesn't exactly fit the model will be considered inlier.
It's the maximum distance a point that doesn't exactly fit the model will be considered inlier.
It's the minimum number or inliers required for a model to be selected.
It's the maximum distance a point that doesn't exactly fit the model will be considered outlier.
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