1. Introduction
1.1. Course organization: Objectives, Overview, Contents, Bibliography, Evaluation, Practical Sessions
2. Basic concepts of Projective Geometry in Computer Vision
2.1. Linear Algebra
2.2. Points and vectors
2.3. Translations and Rotations
2.4. Homogeneous Coordinates
2.5. Inverses and Transposes
3. Image formation and Camera Modelling
3.1. Optical Sensors
3.2. The pinhole model
3.3. Intrinsic and extrinsic parameters
3.4. Computing the calibration matrix
3.5. Effect of camera lenses
4. Image Primitives
4.1. Interest point detectors
4.2. Harris and Hessian detectors
4.3. Similarity measures: SAD, SSD, Correlation
4.4. Introduction to Scale invariant features
5. Feature detectors and descriptors
5.1. Feature detectors
5.2. Invariance
5.3. Descriptors
5.4. Review of SIFT
6. Robust Estimation in Computer Vision
6.1. Probabilistic methods
6.2. Computing the homography matrix
6.3. Outlier rejection: Random Sampling Consensus
6.4. Applications: Planar motion estimation, Mosaicing, etc.
7. Multiple view geometry
7.1. The principle of Triangulation
7.2. Stereo vision
7.3. Epipolar geometry
7.4. Computing the Fundamental matrix
7.5. Trinocular constraints and n-camera constraints
8. Structure-from-Motion
8.1. Review of SfM approaches
8.2. Main components of 3D model creation pipeline
9. Real-time Computer Vision and Vision applied to Robotic systems
9.1. Visual odometry
9.2. Incremental approaches and visual SLAM
9.3. Review and examples of applied to field Robotics
10. Non-conventional optical imaging systems
10.1. Omnidirectional vision systems
10.2. Multispectral and hyperspectral
10.3. Event-based cameras, range gating and others
About evaluation:
50% Exam.
50% Practical Sessions (Every exercise Mark >= 5/10)
Criteris específics de la nota «No Presentat»:
Lab assignments are mandatory. Failure to deliver a lab assignment implies that the student will not be evaluated in the module.
Avaluació única:
Exam of theoretical and practical contents of the subject. In order to be able to do this, it will be necessary to first deliver two alternative labs that will be provided to students who opt for the single assessment.
The final grade will be 80% of the exam and 20% of the labs.
If deemed necessary, a meeting will be organized where teachers can ask questions they deem appropriate about the lab reports delivered.
For the students to be elegible for the single assessment, they should apply within the deadlines set and in accordance with the procedures and criteria established by the Governing Board of the center.
Requisits mínims per aprovar:
To pass the module, the global mark must be >= 5/10