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Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course FMA315F valid from Autumn 2023

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General
  • English
  • If sufficient demand
Aim
  • This course will cover advanced topics in computer vision with a focus on geometry,
Contents
  • Topics covered in the course include simultaneous localization and mapping (SLAM), structure from motion (SFM), and visual localization. Topics will include both traditional methods and recent developments in deep learning-based approaches.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • Understand advanced techniques in computer vision for geometry, including SLAM, SFM, and visual localization
    Understand and discuss the current state-of-the-art and future directions in computer vision for geometry research
    Be familiar with metrics and benchmarks used for evaluation in the field, to measure performance of State-of-the-art methods
Competences and Skills
  • For a passing grade the doctoral student must
  • Be able to apply advanced techniques in computer vision for geometry, including SLAM, SFM, and visual localization
    Analyze and interpret images and videos for 3D reconstruction and scene understanding
    Develop and implement systems for pose estimation and mapping
    Be able to use metrics and benchmarks to measure performance of developed methods.
Judgement and Approach
  • For a passing grade the doctoral student must
Types of Instruction
  • Seminars
  • Self-study literature review
Examination Formats
  • Seminars given by participants
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
Selection Criteria
Literature
  • Vetenskapliga artiklar som belyser både historik och nuvarande forskningsfront inom området.
Further Information
Course code
  • FMA315F
Administrative Information
  • 2023-10-03
  • Maria Sandsten

All Published Course Occasions for the Course Syllabus

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