14:332:472 Introduction to Robotics and Computer Vision

Course catalog description: Introduction to computer vision and robotics. Image formation and analysis. Rigid body and coordinate frame transformations. Low-level vision and edge detection. Models for shading and illumination. Camera models and calibration. 3-D stereo reconstruction. Epipolar geometry and fundamental matrices. Motion estimation.

Credits and contact hours: 3 credits; 1 hour and 20-minute session twice a week, every week

Pre-Requisite courses: 14:332:345, 14:332:346 

Co-Requisite courses: None

Topics Covered:

  • Computer Vision Overview, robot kits
  • Extension of One-Dimensional Signal Processing to Two-Dimensions, Convolution, Image filtering, Discrete Fourier transforms, Sampling theory
  • Linear Algebra, Basic principles
  • Numerical Methods, Least squares estimation, Singular value decomposition
  • Image Analysis, Image pyramids, Image features, Edge and corner detection
  • Rigid body transformations, rotation, translation, homogeneous coordinates
  • Coordinate frame transformations
  • Image Formation and Camera Models, Perspective projection, Homography
  • Camera Calibration 
  • Stereo Vision, Point correspondences, Epipolar geometry
  • Three-Dimensional reconstruction, Generating depth maps
  • Motion, Optical flow, Affine motion models, Image stabilization
  • Feature-based object recognition using statistical inference
  • Appearance-based modeling, Eigenspace methods, Object recognition

Textbook: E. Tresso and A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice-Hall; R. Szeliski. Computer Vision: Algorithms and Applications, Springer; D. Forsyth and J. Ponce, Computer Vision:  A Modern Approach, Prentice-Hall.

Other supplemental material: Learning Open CV, Bradsky & Kaehler, O’Reilly; MatLab: Student Version, Current Edition, The MathWorks, Inc., J. Knudsen