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Introduces the basics of image formation, covering analog and digital images, camera geometry, coordinate systems, and camera calibration.
Introduces camera calibration basics, including parameters estimation, pinhole model limitations, lens imaging, depth of field, and lens distortions.
Covers the diverse applications of Kernel Canonical Correlation Analysis, showcasing its effectiveness in various domains.
Covers the basics of a pinhole camera and the impact of changing parameters on image quality.
Introduces raytracing for generating realistic digital images of 3D scenes.
Introduces the basics of edge detection, including measuring contrast, gradient images, Fourier interpretation, Gaussian functions, Canny edge detector, and industrial applications.
Covers the fundamental concepts of machine learning, including classification, algorithms, optimization, supervised learning, reinforcement learning, and various tasks like image recognition and text generation.
