Computer Vision
1
2019-2020
02000574
Optional
Portuguese
Face-to-face
SEMESTRIAL
6.0
Elective
2nd Cycle Studies - Mestrado
Recommended Prerequisites
Signals and Systems, Signal Processing, Control, Computational Mathematics.
Teaching Methods
The teaching methodologies include theoretical classes using both the blackboard and the projection of slides as well as practical classes where computational assignments are implemented.
Learning Outcomes
Understand aspects related to the radiometric and geometric image formation. Learn methods to estimate image features and relate them to 3D structures. Learn methods for 3D reconstruction and also for the estimation of 3D motion.
Work Placement(s)
NoSyllabus
Formation and acquisition of images. Cameras and geometric calibration. Color and radiometry. Linear filters and edge detection. Texture. Segmentation. Stereo Vision. Motion and its projection. Optical flow. 3D reconstruction. Dynamic Vision.
Head Lecturer(s)
Jorge Manuel Moreira de Campos Pereira Batista
Assessment Methods
Assessment
Exam: 50.0%
Laboratory work or Field work: 50.0%
Bibliography
Computer Vision -A Modern Approach, Forsyth & Ponce, Prentice-Hall
Introductory Techniques for 3-D Computer Vision, Emanuele Trucco & Alessandro Verri, Prentice-Hall
Multiple View Geometry in Computer Vision, R. Hartley & A. Zisserman, Cambridge University Press