Course Outcomes

Derive and describe image formation with regards to world and camera relative geometry;

Describe the process of camera calibration and its related optimization formulations;

Apply stereo triangulation and epipolar constraints for solving vision related problems;

Describe the relationship between the heat equation, diffusion, and Gaussian smoothing;

Apply and implement differential and convolutional operators as discrete stencil operations;

Explain the role of optimization in solving vision-based problems or estimating visual properties; 

Describe the purpose of adding prior constraints or regularization terms to computer vision derived optimization problems; 

Describe fundamental approaches to segmentation and clustering; 

Explain the equations underlying optical flow and their derivation from cost functionals;