These notes accompany the University of Maryland CS class CMSC426: Computer Vision Spring 2019. Thank you to Nitin Sanket and Chahat Deep Singh for creating Project 1, Project 2, and the the Descrption of Rotobrush and SfM. The logistics for the course are available here. Slides from lecture are posted here.
Module 0: Preparation
Module 1: Color Segmentation using GMM
Project 1: Color Segmentation using GMM
color segmentation, bayer filter, image acquisition, color-space
Module 2: Panaroma Stitching
Project 2: Stitching multiple images seemlessly to create a panorama
  • Part I: Learning the basics
    convolution, filtering, features, edges, corners, SIFT, camera model, pinhole model, calibration, projective geometry, homography
  • Part II: Panorama Stitching
    ANMS, feature descriptor, feature correspondence, homography, ransac, cylinderical projection, blending images,
Module 3: Graph-cut Segmentation
Description of a Segmentation Algorithm: Rotobrush
Rotobrush
local classifiers, color confidence, shape confidence, local boundary deformation
SfM or SLAM
Explaining Structure from Motion (SfM) or Simultaneous Localization and Mapping (SLAM)


Fall 2019 Assignments
Homework 1: Linear Least Squares
  •   Release Date: Jan 31, 2019
  •   Deadline: Feb 7, 2019
Project 1: Color Segmentation using GMM
  •   Release Date: Feb 7, 2019
  •   Deadline: Feb 19, 2019
Project 2: Panorama Stitching
  •   Deadline: March 12, 2019
In-class Midterm
  •   March 14, 2018
Project 3: Segmentation
  •   Deadline: April 11, 2019

Recognition

  •   Deadline: May 16, 2019




Perception & Robotics Group
University of Maryland
Copyright © 2018