Skip to content

Geniussh/Computer-Vision

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

67 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Course Projects in Computer Vision at CMU

Any Copying from the work of another person is a violation of Carnegie Mellon University Policy on Academic Integrity.

  • Feature Extraction based on Filter Banks
  • K Means Clustering
  • Visual Word Dictionary
  • Scene Classification
  • Hyperparameters Tuning
  • CNN Implementation

  • Direct Linear Transform
  • Matrix Decomposition to calculate Homography
  • Limitations of Planar Homography
  • FAST Detector and BRIEF Descriptors
  • Feature Matching
  • Compute Homography via RANSAC
  • Automated Homography Estimation and Warping
  • Augmented Reality Application using Homography
  • Real-Time Augmented Reality with High FPS
  • Panorama Generation based on Homography

  • Simple Lucas & Kanade Tracker with Naive Template Update
  • Lucas & Kanade Tracker with Template Correction
  • Two-dimensional Tracking with a Pure Translation Warp Function
  • Two-dimensional Tracking with a Plane Affine Warp Function
  • Lucas & Kanade Forward Additive Approach
  • Lucas & Kanade Inverse Compositional Approach

  • Fundamental Matrix Estimation using Point Correspondence
  • Metric Reconstruction
  • Retrieval of Camera Matrices up to a Scale and Four-Fold Rotation Ambiguity
  • Triangulation using the Homogeneous Least Squares Solution
  • 3D Visualization from a Stereo-Pair by Triangulation and 3D Locations Rendering
  • Bundle Adjustment
    • Estimated fundamental matrix through RANSAC for noisy correspondences
    • Jointly optmized reprojection error w.r.t 3D estimated points and camera matrices
    • Non-linear optimization using SciPy least square optimizer

  • Manual Implementation of a Fully Connected Network
  • Text Extraction from Images of Handwritten Characters
  • Image Compression with Autoencoders
  • PyTorch Implementation of a Convolutional Neural Network
  • Fine Tuning of SqueezeNet in PyTorch
  • Comparison between Fine Tuning and Training from Scratch
  • Calibrated Photometric Stereo
  • Uncalibrated Photometric Stereo
  • Generalized Bas-Relief Ambiguity