Computer Vision - Midterm Exam 2002 | CS 482, Exams of Computer Science

Material Type: Exam; Professor: Duric; Class: Computer Vision; Subject: Computer Science; University: George Mason University; Term: Unknown 1989;

Typology: Exams

Pre 2010

Uploaded on 02/10/2009

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CS 482 Midterm (100p), 10/24/2002
Name:
1. (15p) You are given a camera with adjustable focal length. Describe how it could be used for
size constancy; i.e., to make different objects appear to have the same image sizes. Show the
relevant math.
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pf4
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CS 482 Midterm (100p), 10/24/

Name:

  1. (15p) You are given a camera with adjustable focal length. Describe how it could be used for size constancy; i.e., to make different objects appear to have the same image sizes. Show the relevant math.
  1. (30) You are given the following binary image.

Assume that a coordinate system with x-axis pointing right and a y-axis pointing up is added. The coordinates of the left bottom pixel are (0, 0). Compute the following parameters:

a) (3p) area, b) (3p) perimeter (describe your algorithm), c) (4p) center of mass, d) (10p) second order moments M 11 , M 20 , and M 02. e) (10p) central moments μ 11 , μ 20 , and μ 02.

  1. (50p) You are given a template N and a binary edge image M.

a) (5p) Represent N so that it can be used by the GHT (Generalized Hough Transform) algorithm. b) (15p) Use GHT to find N in M. How many matches did you find? You can use the grid above for the GHT accumulator array. c) (10p) Use forward/backward pass algorithm to compute the distances of all points in M from the edge points of M. You can assume that the distance between any pair of 8-neighbors is 1. d) (15p) Use Chamfer matching to find N in M. Show all placements with scores lower than 10. You can assume that the placement of N is at the position of the topmost pixel of N. What are the best matches? e) (5p) Show how the distance transform array could be used to perform a Hausdorff dis- tance matching on N and M. Show the best match(es).

Template N, edge image M, and the GHT scores.

N M

N and M GHT scores

Distance transform and Chamfer match scores

forward pass backward pass match score

Hausdorff distance matching