Photogrametrics and robot vision

Code:

MVCOMP11

Acronym:

FVR

Keywords
Classification	Keyword
CNAEF	Engineering and related techniques

Instance: 2022/2023 - 2S

Active?	Yes
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Master in Computer Vision

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MVCOMP	0	Syllabus	1	-	6	42	162

Teaching language

English
Obs.: Lecionada por docentes da Universidade de Vigo

Objectives

Presentation of specific photogrammetry topics that are transversal to several application domains, including the main industrial applications.

Learning outcomes and competences

Acquire and understand knowledge as a basis or opportunity to be original in the development and / o r application of ideas, often in a research context.
The students shall know how to co mmunicate their conclusions - and the knowledge and ultimate reasons that sustain them- to specialized and non-specialized audiences in a clear and unambiguous way.
Ability to work in team, organization and planning.
Ability to analyze and synthesize knowledge.
Know and apply the concepts, methodologies and technologies of photogrametrics and robot vision.
Know and apply the concepts, methodologies and technologies of embedded systems and autonomous navigation.
Know and apply the fundamentals of image acquisition and artificial vision systems.
Know and apply the concepts, methodologies and technologies for the recognition o f visual patterns in real scenes.

Working method

À distância

Program

Advanced c amera calibration
Geometric transformations. C orrection of perspective, rectification and metrology.
Relative and absolute orientation. Epipolar geometry and triangulation.
Bundle adjustment and self-calibration. 3D models and industrial applic ations
Embedded systems and architectures.
Integration of sensors and multimodal information.
Visual Odometry Autonomous navigation and SLAM .
Applications of robotic vision.

Mandatory literature

Luhmann,Thomas y Robson, Stuart; Close Range Photogrammetry: Principles, Methods and Applications,1ª ed.,, Whittles Publishing, 2011

Comments from the literature

Other titles to be listed.

Teaching methods and learning activities

Participatory lectures, laboratory practices and in computer ro oms, conferences, learning based on the resolution of practical cases, use of the virtual classroom, autonomous work and independent study of students, group work and collaborative learning, preparation and presentation of work course.
The annual teaching guide of the subject will include the details on the learning methodology. 
Practical classes held in the laboratory at the University of Vigo.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Trabalho prático ou de projeto	100,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Apresentação/discussão de um trabalho científico	10,00
Elaboração de projeto	60,00
Frequência das aulas	36,00
Trabalho laboratorial	6,00
Estudo autónomo	40,00
Trabalho escrito	10,00
Total:	162,00

Eligibility for exams

To be defined.

Calculation formula of final grade

The evaluation will be supported in the projects developed during the
semester.