Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session


Provides a comprehensive introduction to key issues and findings in object recognition in experimental, neural, computational, and applied domains. Emphasizes the problem of representation, exploring the issue of how 3-D objects should be encoded so as to efficiently recognize them from 2-D images. Second half focuses on face recognition, an ecologically important instance of the general object recognition problem. Describes experimental studies of human face recognition performance and recent attempts to mimic this ability in artificial computational systems. An additional project is required for graduate credit.


10%: Class participation
15%: Lead a class discussion and scribe notes for one lecture
10%: Send three questions to scribe after each lecture

  1. Open research question / project idea
  2. A short answer question
  3. A multiple choice question

25%: Mid-term exam
40%: Term project