Core Concepts and Traditional Methods

Chapter 4: Image Formation and Optics (Pinhole cameras, lens models, radiometry, projective geometry) Chapter 5: Feature Extraction and Matching (Harris corners, SIFT, SURF, ORB, BRIEF, RANSAC) Chapter 6: Geometric Vision (Homography, epipolar geometry, stereo vision, camera calibration) Chapter 7: Motion and Optical Flow (Lucas-Kanade, Horn-Schunck, dense flow, motion estimation) Chapter 8: Color and Texture Analysis (RGB, HSV, LAB, texture descriptors, Gabor filters) Chapter 9: Traditional Recognition Techniques (HOG, Haar cascades, Viola-Jones, SVMs, template matching)