1. CS262 – Computer Vision Lect 08: SIFT Keypoint Detection
John Magee
13 February 2017
Slides courtesy of Diane H. Theriault

2. Question of the Day:
How do we find repeatable, stable, scale-invariant points in images?

4. SIFT Find repeatable, scale-invariant points in images (today)
Compute something about them
Use the thing you computed to perform matching
“Distinctive Image Features from Scale-Invariant Keypoints” by David Lowe
Patented!

5. How to find the same cat? Imagine that we had a library of cats
How could we find another picture of the same cat in the library?
Look for the markings?

6. How to find the same cat? Imagine that we had a library of cats
How could we find another picture of the same cat in the library?
Look for the markings?
Which markings?

7. How to find the same cat? Imagine that we had a library of cats
How could we find another picture of the same cat in the library?
Look for the markings?
Which markings?

8. How to find the same cat? Imagine that we had a library of cats
How could we find another picture of the same cat in the library?
Look for the markings?
Which markings?
Which cat would be easier to uniquely identify?

9. Keypoints Idea: Want to find points that are easy to localize uniquely
This one
Not this one

10. Keypoints at Different Scales
Idea: Want to find scale-invariant points that are easy to localize uniquely

11. Gaussian

12. Scale Space
Image convolved with Gaussians of different widths

13. Scale Space Octaves
Every time the width of your Gaussian doubles, downsample the image

14. Derivative of a Gaussian

15. Second Derivative of a Gaussian

16. Laplacian of a Gaussian
Sum of spatial second derivatives

17. Keypoints with Image Filtering
Perform image filtering by convolving an image with a “filter”/”mask” / “kernel” to obtain a “result” / “response”
The value of the result will be positive in regions of the image that “look like” the filter
What would a “dot” filter look like?
Filter

18. Scale-space extrema “Extrema” = local minimum or maximum
Check 8 neighbors at a particular scale
Check neighbors at scales above and below

19. Scale-space Extrema

20. Difference of Gaussians
Approximation of the Laplacian of a Gaussian

21. Discussion Questions:
What does it mean for an image point to be repeatable?
What are the properties of repeatable points?

22. Keypoints with Image Filtering
What tool have we learned about for finding places in the image that “look like” corners or dots?