Reprojecting the Perseverance landing footage onto satellite imagery

Not only impressively coded but a beautiful result as well fascinating to have that real time, frame by frame comparison. Great job!

It only reinforces that I really need to learn my matrix math.

Fascinating and well explained!

Reminded me of the video tracking work these folks do: https://forensic-architecture.org/

Excellent post! I wonder why SIFT didn't find sufficient keypoints early on, it's typically a beast of a method for such a task. It looks like there's some intensity variation, the satellite image is darker, but I'm not sure that would explain it all.

An interesting side point is that the graph optimization approach used here is somewhat similar to modern graph-based visual SLAM

The graph in the article can be seen as a factor graph. VSLAM systems usually have a (kind of bipartite) factor graph with vertices/variables that are either keyframes or ‘good’ features, with edges/factors between features and the frames that see them and between adjacent frames; each of these edges are the factors in the graph. This structure results in very large but sparse graphs, and there are factor graph optimization libraries that take advantage of this sparsity (e.g. g2o or GTSAM.) These libraries also use specialized optimization techniques for some of the nonlinear manifolds (e.g. SO(3)) that arise in SLAM problems.

Did Scott Manley do something similar with the Change 5 landing footage on the Moon.

https://youtu.be/lwLPzU8H3HI