This course focuses on the fundamental mathematical and physical principles of computer vision. It begins by introducing the physical imaging process, encompassing crucial subjects such as color, polarization, radiometry, reflectance models, and photometric methods. Subsequently, it explores the realm of geometric multi-view vision, encompassing topics like features, multi-view stereo, optical flow, structure-from-motion, visual SLAM, and NeRF. Finally, the course delves into the domain of semantic vision, examining classification, recognition, segmentation, CNN, LSTM, and Transformers.