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

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

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!

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?

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?

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?

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?

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

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

Gaussian

Scale Space Image convolved with Gaussians of different widths

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

Derivative of a Gaussian

Second Derivative of a Gaussian

Laplacian of a Gaussian Sum of spatial second derivatives

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

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

Scale-space Extrema

Difference of Gaussians Approximation of the Laplacian of a Gaussian

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

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