youssef3173/computer_vision

Computer Vision Algorithms

Computer Vision:

Computer Vision Algorithms:

• Camera Calibration:

The process of computing the camera intrinsic and extrinsic parameters is called camera calibration. Generally, the camera calibration process uses images of a 3D object with a geometrical pattern (e.g. checker board). The pattern is called the calibration grid. The 3D co-ordinates of the pattern are matched to 2D image points.

• Epipolar Geometry:

Epipolar geometry is the geometry of stereo vision. When two cameras view a 3D scene from two distinct positions, there are a number of geometric relations between the 3D points and their projections onto the 2D images that lead to constraints between the image points. These relations are derived based on the assumption that the cameras can be approximated by the pinhole camera model.

• Distortion Correction (Barrel Pincushion distortion):

In geometric optics, distortion is a deviation from rectilinear projection; a projection in which straight lines in a scene remain straight in an image. It is a form of optical aberration. Distortion Correction is an adjustment that alters the pixels of the image to straighten out lines and reduce the "fish-eye" or "barrel" effect in the image.

• Bundle Adjustment:

Bundle adjustment boils down to minimizing the reprojection error between the image locations of observed and predicted image points, and one of the most known algorithm to minimize this error of reprojection is the Levenberg-Marquardt Algorithm.