Master in Computer Vision

Objectives and competences

Objectives and competences

Objectives

Competences

• Capacity to design all the components of a complete computer vision system in any real-world context that may arise.


• Capacity to plan the development, evaluation and dissemination of solutions to a real computer vision problem.


• Capacity to anticipate and solve problems derived from teamwork in different situations.


• Capacity to identify all the necessary components of a vision system in order to solve a problem.


• Capacity to select the best algorithms for each defined component in order to solve a vision problem.


• Capacity to provide appropriate modelling to solve any part of a vision problem.


• Capacity to recognize the ethical, economic, legal, gender and environmental dimensions of applying vision systems.


• Capacity to establish the state of the art in solving a vision problem.


• Capacity to apply mathematical techniques to solve a vision problem and evaluate the results in all components.


• Capacity to select the best computer tools to encode techniques in order to solve a specific vision problem.


• Capacity to construct the best datasets to train architectures in order to solve a specific vision problem.


• Capacity to estimate the environmental or discriminatory effects that may arise from experiments or data related to the developed systems.


• Capacity to elaborate a document that fully describes the results of the development of a vision project.


• Capacity to defend the results of the development of a vision project through an oral presentation.


• Capacity to determine the most suitable technology transfer process for innovation in a vision project.

Access and admission

Applicant profile and access requirements

Recommended applicant profile

This master's degree is addressed to students who are interested in computer vision and have the following profile:

Students' interests

• Studies in mathematics, physics or any engineering discipline; interest in specializing in artificial intelligence with a view to pursuing a technical career.
• Current employment in this field; interest in updating knowledge.
• Enrolled in a doctoral thesis in this field and requiring a master's degree needed to complete the requisite number of ECTS credits.

 

Academic profile

• High-level knowledge of programming and mathematics (algebra, signal theory, basic image processing, probability and statistics).
• Knowledge of prototype-based programming languages, such as Python or Matlab.
• Knowledge of English at B1 or higher in the European Framework of Reference for Languages (comprehension, written expression and spoken expression).

 

Personal skills

• Motivation to deal with complex problems.
• Autonomy to plan work.
• Empathy in order to interact effectively as part of a team.
• Dedication.
• Flexibility and creativity versus results.

Access requirements and conditions

General requirements
In accordance with Article 16 of Royal Decree 1393/2007, of 29 October, students wishing to be admitted to a university master's degree must hold one of the following qualifications:

• Official Spanish university degree.


• A degree issued by a higher education institution within the European Higher Education Area framework that authorizes the holder to access university master's degree courses in the country of issue.


• A qualification issued by an institution outside the framework of the European Higher Education Area. In this case, applicants must request homologation of the degree to its equivalent official Spanish university qualification or obtain express approval from the University of Barcelona, which will conduct a study of equivalence to ensure that the degree is of a comparable level to an official Spanish university qualification and that it grants access to university master's degree study in the country of issue. Admission shall not, in any case, imply that prior qualifications have been recognized as equivalent to a Spanish master's degree and does not confer recognition for any purposes other than that of admission to the master's degree course.

Specific requirements
The access requirements are as follows:

1. Bachelor's degree in engineering, mathematics or physics, or equivalent.

2. B1 English language proficiency (as defined in the Common European Framework of Reference for Languages).

Pre-enrolment

Calendar

Required documentation

Selection criteria

If the number of applicants exceeds the available places offered, students will be assigned a place on the basis of the following criteria:

• Academic record (30%).


• Degree in a subject directly related to the field of study (20%).


• Professional or research experience in this field, including programming skills in prototyping languages like Matlab or Python (20%).


• English at level B2 or higher, according to the Council of Europe's Common European Framework of Reference for Languages (20%).


• Degree of motivation to develop expertise in the field of study (10%).

Notification

Enrolment

As a general rule, at the UB you will be required to enrol online. Remember that you can lose your place if you do not enrol on the day you have been assigned

• Documents required for enrolment
• Procedure to formalize enrolment
• Grants and financial aid (in Catalan)
• Economic information (in Catalan)

Welcome

• Student Support Service
• Grants and financial aid (in Catalan)
• Accommodation

Course curriculum

Subjects and course plans

Distribution of credits

List of subjects

Subject	Type	Language	Credits
Specialization: Computer Vision
3D Vision	Compulsory		6
Introduction to Human and Computer Vision	Compulsory		6
Machine Learning for Computer Vision	Compulsory		6
Master's Degree Dissertation	Compulsory		9
Optimisation Techniques for Computer Vision	Compulsory		6
Research Dissemination and Transfer	Compulsory		9
Video Analysis	Compulsory		9
Visual Recognition	Compulsory		9

Previous years

Teaching staff

List of spring and autumn teaching staff on a current course

Placements

Placements in a company or another type of organization are an integral part of university studies, providing first-hand experience of working methodologies in students' chosen professional fields. They offer invaluable practical experience for the transition into work after graduation.

Placements are supervised by tutors and subject to assessment. They are therefore included in the academic record.  There is also an option to complete non-curricular placements of up to 500 hours, which can be extended to 900 hours. For both curricular and non-curricular placements, an educational cooperation agreement is signed between the UB and the company, institution or other organization at which the placement will be carried out.

Institutional information

• Regulations on external placements


• FeinaUB

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