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OpenCV with Python Blueprints by Michael Beyeler

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Summary

In this chapter, we explored a way of reconstructing a scene in 3D—by inferring the geometrical features of 2D images taken by the same camera. We wrote a script to calibrate a camera, and you learned about fundamental and essential matrices. We used this knowledge to perform triangulation. We then went on to visualize the real-world geometry of the scene in a 3D point cloud. Using simple 3D scatterplots in matplotlib, we found a way to convince ourselves that our calculations were accurate and practical.

Going forward from here, it will be possible to store the triangulated 3D points in a file that can be parsed by the Point Cloud Library, or to repeat the procedure for different image pairs so that we can generate a denser and more accurate ...

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