Course Outline
Computational Perception
COMP 546 (4 credits)
Winter 2018
Tues/Thurs 8:35-9:55   ENGTR 1080

Instructor:    Professor Michael Langer
Office:        McConnell Engineering, rm. 329
Tel:             514-398-3740
Office Hours:           Tues and Thurs 10 AM -11 AM or by appointment

Teaching Assistant (T.A.)   TBD
Email:                                 TBD [at]
Office and Hours:               by appointment

Official Course Description from McGill Calendar

Computational models of visual perception and audition. Vision problems include stereopsis, motion, focus, perspective, color. Audition problems include source localization and recognition. Emphasis on physics of image formation, sensory signal processing, neural pathways and computation, psychophysical methods.


This course examines fundamental computational problems in visual and auditory perception. Unlike traditional perception courses offered in Psychology or Physiology departments which emphasize neural mechanisms, this course emphasizes computational aspects of perception. The course consists of two main topics, namely vision and audition. For both of these perceptual modalities, we begin by examining the signals from the environment, namely visual and auditory images, and the information that is contained in these images.   For vision, we consider color, shading, binocular disparity, motion, and focus.   For audition, we consider information carried by impact vs, non-impact sounds, echos, as well as binaural timing and intensity differences. For both vision and audition, we then examine how images are processed by the sensory system, using concepts and tools from linear system theory.   For vision, we discuss retinal and cortical processing. For audition, we discuss how sound waves are decomposed into frequency bands by the ear and encoded by the auditory cortex. We then examine how properties of the environment can be inferred from the information that is extracted from images.  For vision, we consider how depth is estimated and for audition, we consider how depth and direction are estimated.    We will also briefly discuss problems of object and scene recognition.

Detailed Course Content and Materials

The course will consist of 25 lectures, each 80 minutes. Lecture slides, notes, and exercises will be given as PDFs on the public course web page . Students will be examined on this posted material. There is no textbook for the course.


There are no official prerequisites for the course. However, it is assumed students can program in a high level language, at least that level of COMP 250, and are comfortable with basic mathematics needed for an undergrad degree in computer science, in particular: The course will cover basic psychology and physiology of vision and audition. It will also cover the basic tools of linear system theory (convolution, Fourier transforms). No prior knowledge of these topics is assumed.


The course grade will be determined as follows:

Other Policies/Rules

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