Estimate the accuracy of the simple stereo system (Figure 3) assuming that the only source of noise is the localization of corresponding points in the two images. Discuss the dependence of the error in depth estimation as a function of disparity error, depth itself, the baseline width and the focal length, respectively.Hint: Z = fB/d; Take the partial derivatives of Z with respect to d, B, f, respectively. **Stereo Vision Geometry**The figure illustrates the concept of stereo vision geometry, particularly focusing on a stereo system with parallel optical axes.**Components:**- **P(X,Y,Z):** The point in space being observed.- **Left Camera:** - Optical Center \( O_l \). - Image Plane: Plotted with point \( p_l(x_l,y_l) \).- **Right Camera:** - Optical Center \( O_r \). - Image Plane: Plotted with point \( p_r(x_r,y_r) \).**Key Elements:**- **Baseline (\( B \)):** The distance between the optical centers of the left and right cameras.- **Focal Length (\( f \)):** The distance from the optical center to the image plane in both cameras.- **Disparity (\( d \)):** Calculated as \( d = x_r - x_l \), representing the difference in the x-coordinates of points on the image planes.- **Depth (\( Z \) or \( D \)):** Estimated using the formula \( Z = D = \frac{f \cdot B}{d} \), associating depth with the disparity and baseline.**Note:**The figure includes a suggestion to redraw so that the point P is not positioned in the middle, optimizing the diagram for clarity and understanding.This diagram serves as an educational tool to explain how stereo cameras can be used to estimate the depth and position of objects in three-dimensional space by using parallel optical axes.

The question is solved in step2 disparity: difference in image placement of the same 3D. point when projecting under perspective to two different cameras. d = xleft - xright. Depth perception arises from the "disparity" of a given 3D point in the right and left retinal images. Disparity is the horizontal displacement of point projections between the left and right images. While depth refers to the z coordinate (usually z) of a point located in the real 3D world (x,y,z). Depth estimation from images is a long-standing problem in computer vision. Depth perception is useful for scene understanding, scene reconstruction, virtual and augmented reality, obstacle avoidance, self-driving cars, robotics, and other applications.