RI_Vision Courses Webpage

Undergraduate Level Courses

Course Number	Course Name	Offerings
15-385	Computer Vision		Every Spring Most recent offer: Spring 2012
15-462/862	Computational Photography		Every Fall Most recent offer: Fall 2011
16-421	Vision Sensors		Most recent offer: Spring 2009


15-385 Computer Vision




Instructor: Srinivasa Narasimhan, Tai-sing Lee
University Units : 12
Semester Offered:
Every spring. Most recent offer: Spring 2012
Course Description
Basic concepts in machine vision, including sensing and perception, 2D image analysis, pattern classification, physics-based vision, stereo and motion, and solid model recognition.

Prerequisites:
15-213: Introduction to Computer Systems 21-214: Matrix Algebra (i.e. matrix & vector algebra) 21-259: Calculus in Three Dimensions (i.e. planes, quadratic surfaces, basic 3-D geometry, partial derivatives) or equivalent.
Topic Covered:
Cameras and their Optics Biological Cameras Image Processing Surface Reflectance Lightness and Perception 3D from Shading Binocular Stereo Optical Flow Range Scanning and Structured Light Statistical Techniques Recent Trends in Vision

For more information, visit the course homepage:
http://www.cs.cmu.edu/afs/cs/academic/class/15385-s12/www/

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15-462/862 Computational Photography



Instructor: Alexei (Alyosha) Efros
University Units : 12
Semester Offered:
Every fall. Most recent offer: Fall 2011
Course Description
Computational Photography is an emerging new field created by the convergence of computer graphics, computer vision and photography. Its role is to overcome the limitations of the traditional camera by using computational techniques to produce a richer, more vivid, perhaps more perceptually meaningful representation of our visual world. The aim of this advanced undergraduate course is to study ways in which samples from the real world (images and video) can be used to generate compelling computer graphics imagery. We will learn how to acquire, represent, and render scenes from digitized photographs. Several popular image-based algorithms will be presented, with an emphasis on using these techniques to build practical systems. This hands-on emphasis will be reflected in the programming assignments, in which students will have the opportunity to acquire their own images of indoor and outdoor scenes and develop the image analysis and synthesis tools needed to render and view the scenes on the computer.

Prerequisites:
15-213: Introduction to Computer Systems 21-214: Matrix Algebra (i.e. matrix & vector algebra) 21-259: Calculus in Three Dimensions (i.e. planes, quadratic surfaces, basic 3-D geometry, partial derivatives) or equivalent.
Topic Covered:
Cameras, Image Formation Image and Video Processing (filtering, anti-aliasing, pyramids) Image Manipulation (warping, morphing, massacring, matting, composition) Data-driven Synthesis Visual Perception High Dynamic Range Imaging and Tone mapping Image-Based Lighting Image-Based Rendering Non-photo realistic Rendering

For more information, visit the course homepage:
http://graphics.cs.cmu.edu/courses/15-463/2011_fall/463.html

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16-421 Vision Sensors



Instructor: Srinivasa Narasimhan
University Units: 12
Semester Offered:
Most recent offer: Spring 2009
Course Description
This course covers the fundamentals of vision cameras and other sensors - how they function, how they are built, and how to use them effectively. The course presents a journey through the fascinating five hundered year history of "camera-making" from the early 1500's "camera obscura" through the advent of film and lenses, to today's mirror-based and solid state devices (CCD, CMOS). The course includes a significant hands-on component where students learn how to use the sensors and understand, model and deal with the uncertainty (noise) in their measurements. While the first half of the course deals with conventional "single viewpoint" or "perspective" cameras, the second half of the course covers much more recent "multi-viewpoint" or "multi-perspective" cameras that includes a host of lenses and mirrors.
Prerequisites:
15-213: Introduction to Computer Systems 21-214: Matrix Algebra (i.e. matrix & vector algebra) 21-259: Calculus in Three Dimensions (i.e. planes, quadratic surfaces, basic 3-D geometry, partial derivatives) or equivalent.
Topic Covered:
PART 1: Perspective Sensors Basic Principles of Still and Video Cameras CCD, Film, CMOS Sensors Electronics (A/D conversion, integration time, sampling, etc) Noise Device response Focus and Depth of Field Scheimpflug Photography Basic Principles of Optical Elements: Filters and Lenses Filters (Polarizers, Neutral Density, Linear Interference) Fish Eye Lenses Single Lens Reflex Lens Distortions, Vignetting, Chromatic Abberations Autoexposure, Autofocus, Optical Stabilization Optical Transfer Function (OTF/MTF) Diffraction-limited Imaging Thermal, Hyperspectral Cameras Camera Calibration Projection Fundamentals and Image Formation Geometric Calibration Radiometric Calibration CCD Demosaicing High Dynamic Range Imaging Sequential change in exposures Spatially varying exposures Real time exposure control over space and time Other sensors Range Finders (structured light, time-of-flight) Pulsed and Gated Imaging PART 2: Non-Perspective Sensors Light Field Plenoptic function Light Field Parameterization Single Viewpoint Catadioptric Cameras Omnicams Multi-viewpoint systems Mathematical background on Caustics Refracting/Reflecting Caustics Multi perspective Images Mosaicing Panoramic/Stereo Mosaicing Pushbroom cameras Projectors and Displays Stereoscopic Displays 3D displays DMD for cameras, displays, projectors Projector-Camera Systems

For more information, visit the course homepage:
http://www.cs.cmu.edu/~ILIM/courses/vision-sensors/

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