DD2429 Computational Photography 6.0 credits
Datorfotografi
Geometric problems in computer vision and image-based visualization such as virtual reality and computer games by 3D reconstruction from multiple views and image-based rendering.
Educational level
Second cycleAcademic level (A-D)
CSubject area
Computer Science and Engineering
Grade scale
A, B, C, D, E, FX, F
Course offerings
Autumn 13 dfoto13 for programme students
Periods
Autumn 13 P1 (6.0 credits)
Application code
50132Start date
2013 week: 36End date
2013 week: 44Language of instruction
EnglishCampus
KTH CampusNumber of lectures
Number of exercises
Tutoring time
DaytimeForm of study
NormalNumber of places
No limitationSchedule
Schedule (new window)Course responsible
Stefan H Å Carlsson <stefanc@kth.se>
Target group
Compulsary for TMAIM-PC2.
Searchable for students at Master of Science in Engineering with at least 90 hp of which at least 50 hp from year 1 and for students at Master of Science in Engineering.
Part of programme
- Master (Two Years), Computer Science, year 2, CSCA, Conditionally Elective
- Master (Two Years), Human-Computer Interaction, year 2, HCIC, Optional
- Master (Two Years), ICT Innovation, year 2, DMTE, Optional
- Master (Two Years), Machine Learning, year 2, MAIA, Mandatory
- Master (Two Years), Machine Learning, year 2, MAIB, Conditionally Elective
- Master (Two Years), Machine Learning, year 2, MAIC, Conditionally Elective
- Master (Two Years), Media Technology, year 1, META, Conditionally Elective
- Master (Two Years), Media Technology, year 2, META, Conditionally Elective
- Master (Two Years), Systems, Control and Robotics, year 1, Recommended
- Master (Two Years), Systems, Control and Robotics, year 2, Recommended
- Master of Science in Engineering and of Education, year 4, MADA, Conditionally Elective
Learning outcomes
After the completion of the course the student is expected to
- describe the research area of image-based 3D visualization and commercial systems for this,
- give an account for the mathematical and geometric foundations used in image-based 3D reconstruction and visualization,
- apply known methods for mathematical and numerical treatment of problems of geometric nature,
- implement methods for automatic extraction of geometric information from images,
- describe how a system for automatic creation of 3D models from known images might look like,
- describe the most common methods for image-based rendering.
Course main content
- Overview of problems and methods in geometric computing such as image based visualization and automatic shape recognition.
- Basic algebra and geometry of imaging systems.
- Geometric basis of texture mapping.
- Mathematics and geometry of multiple views.
- Calibration and 3D reconstruction from multiple views.
- Methods for analysis of geometric shape.
- Robust statistics and matching problems.
- Methods for image-based rendering.
Eligibility
Single course students: 90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.
Prerequisites
Knowledge corresponding to the compulsory courses on mathematics, computer science and numerical analysis on D-, E- or F-programme.
Literature
Course notes produced at the department.
Examination
- LAB1 - Laboratory Works, 3.0 credits, grade scale: P, F
- TEN1 - Exam, 3.0 credits, grade scale: A, B, C, D, E, FX, F
In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.
Offered by
CSC/Computer Science
Contact
Stefan Carlsson, tel: 790 8432, e-post: stefanc@kth.se
Examiner
Stefan H Å Carlsson <stefanc@kth.se>
Supplementary information
The course has replaced DD2428 Geometric Computing and Visualization.
The course is given in English if necessary.
Add-on studies
DD2423 Image Processing and Computer Vision and
DH2413 Advanced Graphics and Interaction.
Version
Course plan valid from:
Autumn 10.
Examination information valid from:
Autumn 10.
