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Page 1 of 5 [PTO] 
 
COMP61342 
 
Formative Assessment 
 
UNIVERSITY OF MANCHESTER 
SCHOOL OF COMPUTER SCIENCE 
 
M.Sc. in Advanced Computer Science 
 
 
Computer Vision 
 
18th May 2020 
 
 
Please answer ALL questions provided 
 
Please submit a SINGLE PDF document with your answers 
 
 
COMP61342 
Page 2 of 5 [PTO] 
 
1. 
 
A student has a set of shapes extracted from a database of images, and wishes to study the 
variation of shape across the database. An expert has already annotated each shape example 
with suitable landmarks. 
 
a) Why is it necessary to align a set of shapes before building a model of shape variation? 
Describe in detail how such alignment could be done. 
[5 marks] 
 
After successful alignment, the student now has a dataset of shapes thus: 
 
She now decides to apply Principal Component Analysis (PCA) to this dataset. 
 
b) Explain in detail how PCA could be applied to this dataset. 
How are the properties and output of PCA of use in the resultant statistical model of 
shape? 
[5 marks] 
 
c) Explain in detail how the mathematical methods and statistical modelling methods 
described above can be used to build a computer vision system suitable for finding a new 
example of an object in a new image. 
What are the main disadvantages of such a model-based vision system? 
[10 marks] 
 
 
End of Question 1 
 
 
 
 
 
COMP61342 
Page 3 of 5 [PTO] 
 
2. 
 
a) Briefly describe the main steps of performing image segmentation using mean- 
shift clustering algorithm. [6 marks] 
 
b) What are the advantages and disadvantages of 
i. EM clustering algorithm [4 marks] 
ii. Normalised cuts segmentation algorithm [4 marks] 
 
c) Consider the data in figure 1. 
 
 
 
 
Figure 1 
 
What do you expect to happen if we run the K-means algorithm with two 
clusters on this data set? Explain why you expect this to happen. [6 marks] 
 
 
 
 
 
End of Question 2 
COMP61342 
Page 4 of 5 [PTO] 
 
3. 
Figure 2 shows a pair of stereo images from the surface of mars that have been 
captured using a pair of calibrated cameras. 
 
a) Explain what “calibrated cameras” means. [2 marks] 
 
b) Define disparity in stereo vision. [2 marks] 
 
c) Describe a method for detecting interest points in an image. [6 marks] 
 
d) Explain how you could use the pair of images in figure 2 to calculate the 
distances from the camera of the surface features that appear in the scene. 
 
 
Figure 2 
 
 
In your answer you need to consider all steps in the process, from images to 
depth values. You also need to give a diagram to illustrate your answer. 
[10 marks] 
 
 
 
End of Question 3 
 
 
COMP61342 
Page 5 of 5 [PTO] 
a) Give a brief outline of the three main constituents of a non-rigid pairwise image- 
registration algorithm. Compare and contrast an algorithm that uses a non-parametric 
representation of image warps, with one that uses a parametric representation. 
[6 marks] 
 
 
b) Describe, using diagrams or otherwise, a simple linear warping algorithm for defining 
a one-to-one mapping between two triangulated meshes. You need only consider one 
triangle of the entire mesh, and how to map to the corresponding point(s) in a second 
triangle of another mesh. 
[4 marks] 
 
 
c) Outline at least three distinct applications of non-rigid image registration to 
biomedical imaging, making clear in each case why registration is required/useful. 
 
[6 marks] 
 
 
d) Why might we wish to perform registration across an entire population? In such a 
case, would fully groupwise registration be a better choice than repeated pairwise 
registration? Give the reasons for your answer. 
[4 marks] 
 
 
 
End of Question 4 
 
 
END OF EXAMINATION 
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