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Course materials for MIPT Camera Geometry In Computer Vision course (Cognitive Technologies)

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camgeom

Course materials for MIPT Camera Geometry for Scene Reconstruction course (Cognitive Technologies)

Practical Task 1: geometry_and_monocular

Basic principles of pinhole camera projection and Homographies are illustrated. The final task is to project image points from lidar to camera on example from KITTI dataset

Practical Task 2: camera_calibration

Camera calibration with a chessboard pattern is performed, using opencv gradients calculation as well as numerical derivatives. Optimisation is performed via scipy.optimize

Practical Task 3: depth_map

This is an illustration of how depth map is calculated using opencv SGBM functions. It doesn't contain programming taks, but requires answering some theoretical questions.

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Course materials for MIPT Camera Geometry In Computer Vision course (Cognitive Technologies)

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