CS 332

Exam 2 Coverage

Exam 2: Thursday, November 15

The second exam will be held in class on Thursday, November 15. It will be an open book exam – you can refer to any of your handouts, readings, notes, assignments and solutions during the exam. The exam will focus on the recovery of observer motion and 3D scene layout from image motion, object recognition, face detection and recognition, and artificial neural networks. The recognition component will cover the modeling approaches that we talked about (e.g. feature- or parts-based approaches, the alignment method based on linear combinations of views, PCA-based face recognition, and recognition with simple neural nets. You should also be familiar with the Viola & Jones face detection method. The exam will not cover deep learning and convolutional neural networks. One problem will include questions related to the perceptual papers that you read for Assignment 4. You do not need to remember specific facts about the neural processing underlying face recognition in the brain, but I may describe a neural behavior and ask you to relate it to a model. The exam will not include any MATLAB programming. The following material will be most useful for preparing for the exam:

Lecture handouts and your lecture notes related to observer motion and recognition — on the course schedule page, this includes classes #15 (not including the slides on motion measurement in the human system), #16, #17 (not including the Exam 1 review), #18, and #20-28

Assignment #4 and the two labs on observer motion and neural networks (and solutions)

Readings:

  1. Patrick Winston's Artificial Intelligence text provides concise introductions to the alignment method for recognition that we discussed, and to simple neural networks — see pages 443-453 and 531-539 of the text (pages 369-379 and 433-441 of the long pdf file)
  2. For a review of face processing, the following paper will be distributed in class on November 7th, with relevant sections marked (includes only a small portion of the full paper):

    Tsao, D. Y. & Livingstone, M. S. (2008) Mechanisms of Face Perception

  3. Readings on perceptual studies of face recognition from Problem 3 of Assignment 4 (you do not need to review the Sinha et al. paper)
  4. The Eigenface wikipedia page provides a short introduction to the Eigenfaces method for face recognition (you can skip the sections on MATLAB example code, Computing the eigenvectors, and Connection with SVD)
  5. The wikipedia page on the Viola-Jones object detection framework provides a short introduction to this method

We will hold a review for the exam on Monday, November 12th.