COMP0028 Computational Photography and Capture
This database contains the 2018-19 versions of syllabuses.
Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).
|Module||Computational Photography and Capture|
|Module delivery||1819/A7U/T2/COMP0028 Masters (MEng)|
|Related deliveries||1819/A7P/T2/COMP0028 Postgraduate|
|Module leader||Weyrich, Tim|
|Module administrator||Ball, Louisa|
The module is designed to be self-contained, introducing the theoretical and practical aspects of modern photography and capture algorithms to students with only limited background in visual computing. The two primary aims are i) to introduce universal models of colour, computer-controlled cameras, lighting and shape capture, and ii) to motivate students to choose among the topics presented for either continuing study (for those considering MSc’s and PhD’s) or future careers in the fields of advanced imaging.
On successful completion of the module, a student will be able to:
Understand principles of light transport in natural scenes
Understand principles of digital image formation
Understand how computational-photography algorithms can exploit knowledge use of these principles to transcend the capabilities of traditional photography
Develop their own small software prototypes to capture and process digital images
Availability and prerequisites
This module delivery is available for selection on the below-listed programmes. The relevant programme structure will specify whether the module is core, optional, or elective.
In order to be eligible to select this module as optional or elective, where available, students must meet all prerequisite conditions to the satisfaction of the module leader. Places for students taking the module as optional or elective are limited and will be allocated according to the department’s module selection policy.
|Programmes on which available:||
Introduction to Computational Photography
Cameras, sensors and colour
Blending and compositing
Background subtraction and matting
Warping, morphing, mosaics and panoramas
High-dynamic range imaging/tome mapping
Flash photography and stylised rendering using multi-flash
Heeger and Bergen
Simplicial complex of morphable textures (Matusik 2005)
Extension to the temporal domain
TIP, Video textures
Temporal sequence rendering
Ezzat speech anim, comtrolled video sprites
Video-based rendering: using photographs to enhance videos of a static scene
Non-photorealistic rendering and animation
Colourisation and colour transfer-colorisation using optimisation
Colour transfer between images
N-Dimensional probability density function transfer and its application to colour transfer
Vectorising Raster images
Poisson image editing
Coded aperture imaging
Image-based modelling and photo editing view dependence, light-dependence, plenoptic function
Selected ways to capture the above representations
Extensions to the temporal domain
Factored time-lapse video
Computational time-lapse video
Video synopsis and indexing
Capturing images with structured light
Brief recap of stereo, spatio-temporal stereo
The Helmholtz wheel (Helmholtz reciprocity)
Seeing around corners
Dual light stage
Separation of global and local reflectance
Image-based BRDF measurements
Measuring the BSSRDF
An indicative reading list is available via http://readinglists.ucl.ac.uk/departments/comps_eng.html.
The module is delivered through a combination of lectures, tutorials, written and programming exercises, and project work.
This module delivery is assessed as below:
|1||Individual project||60||Submission takes place in two parts.|
In order to pass this Module Delivery, students must:
- achieve an overall weighted Module mark of at least 50.00%;
AND, when taken as part of MEng Computer Science and MEng Mathematical Computation:
- achieve a mark of at least 40.00% in any Components of assessment weighed ≥ 30% of the module.
Where a Component comprises multiple Assessment Tasks, the minimum mark applies to the overall component.