1. Introduction
1.1. Course organization: Objectives, Overview, Contents, Bibliography, Evaluation, Practical Sessions
1.2. Review of rigid body transformations
2. Camera Modelling and Calibration
2.1. The pinhole camera
2.2. Intrinsic and extrinsic parameters
2.3. Computing the calibration matrix
2.4. Accuracy Evaluation
3. Image Primitives
3.1. Interest point detectors
3.2. Harris and Hessian detectors
3.3. Similarity measures: SAD, SSD, Correlation
3.4. Introduction to Scale invariant features
4. Correspondence and Planar Transformations
4.1. Review of SIFT
4.2. A hierarchy of transformations: Euclidean, Similarity, Affine, Projective
5. Outlier Rejection
5.1. Probabilistic methods
5.2. Computing the homography matrix
5.3. Random Sampling Consensus
5.4. Applications: Planar motion estimation, Mosaicing, etc.
6. Reconstruction from 2 views
6.1. The principle of Triangulation
6.2. Epipolar geometry
6.3. Computing the Fundamental matrix
6.4. Accuracy Evaluation
6.5. Experimental Results
7. Cameras in the real world
7.1. Comercial cameras
7.2. Camera characteristics
8. Pattern Projection Techniques
8.1. The principle of codification
8.2. State of the art
8.3. Time multiplexing, spatial codification, direct codification
8.4. Steps to implement a pattern projection technique