|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.
||A mini-lecture on object moments and the associated properties: centroid location, orientation and elongation.
||Vision with sequences of images, including real and apparent motion, background subtraction and optical flow estimation, (feature) tracking, structure from motion and SLAM.
|The purpose of this Consolidation session is to test your understanding of the material presented in the Module.
||An overview of stereo vision, covering the depth and disparity estimation, the correspondence problem, window-based and scanline stereo.
||Machine learning for computer vision, including classification vs regression, discriminative vs generative methods, advanced feature encoding, action and gesture recognition,
datasets and annotation.