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:
Tsao, D. Y. & Livingstone, M. S. (2008) Mechanisms of Face Perception
We will hold a review for the exam on Monday, November 12th.