CS-E4850 - Computer Vision D, 07.09.2020-11.12.2020

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Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After the course, the student is familiar with basic concepts and methods of computer vision. The student understands the basic principles of image-based 3D reconstruction and is familiar with techniques used for automatic object recognition from images. The student can design and implement common computer vision methods and apply them to practical problems with real-world image data.

Credits: 5

Schedule: 07.09.2020 - 11.12.2020

Teacher in charge (valid 01.08.2020-31.07.2022): Juho Kannala

Teacher in charge (applies in this implementation): Juho Kannala

Contact information for the course (applies in this implementation):

CEFR level (applies in this implementation):

Language of instruction and studies (valid 01.08.2020-31.07.2022):

Teaching language: English

Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • Valid 01.08.2020-31.07.2022:

    Image formation and processing, feature detection and matching, motion estimation, structure-from-motion, object recognition, image-based 3D reconstruction. The course gives an overview of algorithms, models and methods, which are used in automatic analysis of visual data.

Assessment Methods and Criteria

  • Valid 01.08.2020-31.07.2022:

    Combination of exercises and exam (details are provided on the first lecture).

Workload

  • Valid 01.08.2020-31.07.2022:

    24 + 24 (2 + 2) 

DETAILS

Study Material
Prerequisites

  • Valid 01.08.2020-31.07.2022:

    Programming skills and basic knowledge of data structures and mathematics (linear algebra, probability) are necessary. 

SDG: Sustainable Development Goals

    9 Industry, Innovation and Infrastructure

FURTHER INFORMATION

Description

Registration and further information

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof