# 代写COMP61342 帮写Processing

Page 1 of 5 [PTO]

COMP61342

Formative Assessment

UNIVERSITY OF MANCHESTER
SCHOOL OF COMPUTER SCIENCE

Computer Vision

18th May 2020

COMP61342
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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
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2.

a) Briefly describe the main steps of performing image segmentation using mean-
shift clustering algorithm. [6 marks]

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
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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
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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
[4 marks]

End of Question 4

END OF EXAMINATION

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