IDENTIFYING DATA 2017_18
Subject (*) ARTIFICIAL VISION AND PATTERN RECOGNITION Code 17665209
Study programme
Computer Engineering: Computer Security and Intelligent Systems (2013)
 Cycle 2nd
Descriptors Credits Type Year Period
4.5 Optional 1Q
Language
Català
Department Computer Engineering and Mathematics
Coordinator
PUIG VALLS, DOMÈNEC SAVI
 E-mail domenec.puig@urv.cat
Lecturers
PUIG VALLS, DOMÈNEC SAVI
Web http://consultar l'espai Moodle de l'assignatura
General description and relevant information To introduce the fundamental concepts of Computer Vision and further advanced topics related to problems of analysis and automatic recognition of complex images. Theoretical concepts and practical applications will be studied by means of well-known tools of Image Processing and Computer Vision.
In this subject you only have the right to make the exam, because the degree you are studying is going to be extinguished. You have to take a look the timetable of the subject to know the exam's date. If you need an extraordinary exam session, you have to enrol for this, presenting an application to the secretariat of your campus or faculty.

Continguts
Topic Sub-topic
Chapter 1.- Image Processing. Filtering, image compensation and image enhancement, morphological operations.
Chapter 2.- Geometrical Feature Extraction. Identification of corners, lines and basic geometrical shapes.
Chapter 3.- Color and Texture Analysis. Color models, texture types, extraction of textural features, geometric methods.
Chapter 4.- Image Segmentation and Classification. Unsupervised segmentation based on contours and regions, supervised classification, methods of decision theory, probabilistic methods, neural networks.
Chapter 5.- Stereoscopic Vision. Calibration of cameras and camera systems, epipolar geometry, image rectification, matching, triangulation.
Chapter 6.- Perception and 3D-modeling. Generation of depth maps, extraction of basic geometric elements,
automatic generation of scenes, scene recognition, geometric hashing.

Atenció personalitzada
Description
Enquiries /Tutorials: Resolution of theoretical and practical questions. Correction of practices. Exams review.

Avaluació
 
Other comments and second exam session

Students who fail the continuous assessment can recover parts suspended or not presented in the second call.

In all written examinations can not bring any electronic device.


Fonts d'informació
Basic D.A. Forsyth, Computer Vision: A Modern Approach, Pearson Education, 2012
R. Szeliski, Computer vision: algorithms and applications, Springer, 2011
N.J. Hackensack, Handbook of pattern recognition and computer vision, Imperial College Press, 2010
L. Shapiro, G. Stockman, Computer Vision, Prentice Hall, 2001
E. Trucco, A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice Hall, 1998

Complementary E.R. Davies, Machine Vision: Theory, Algorithms, Practicalities, Academic Press, 1997
O. Faugeras, Three-Dimensional Computer Vision, MIT Press, 1993

(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.