|An overview of the field, including the typical structure of vision algorithms, an overview of the applications, difference b/w low-level and mid-level vision.
||The image formation process, including perspective projection, camera calibration, the physics of image formation, camera models.
||Vision with sequences of images, including real and apparent motion, background subtraction and optical flow estimation, (feature) tracking, structure from motion and SLAM.
||Machine learning for computer vision, including classification vs regression, discriminative vs generative methods, advanced feature encoding, action and gesture recognition,
datasets and annotation.