ETH-CV-exercise-review

My solutions to exercises of Computer Vision course @ ETH Zurich

Exercises

Ex 01 - Camera calibration

DLT, Golden standard, Camera model, Calibration

Ex 02 - Local Features

Harris corner, Feature descriptor, Feature matching

Ex 03 - Particle Filter

Particle filter, Bayes law, Localization

Ex 04 - Model Fitting

RANSAC line fitting, Fundamental matrix, Epipolar geometry, 8-point method, Adaptive RANSAC

Ex 05 - Image Segmentation

Meanshift, Expectation Maximization (EM)

Ex 06 - Stereo Matching

MVS, Disparity map, Winner-take-all local method, Graph-cut global method, Dense reconstruction

Ex 07 - Structure from Motion

SfM, Initialization, Essential Matrix, PnP problem, Triangulation, Dense reconstruction

Ex 08 - Specific Object Recognition

Template shape matching, Shape context, TPS transformation estimation

Ex 09 - Shape from Silhouettes

Shape from silhouettes

Ex 10 - Image Categorization

Histogram of Oriented Gradient(HOG), KMeans, Bag of Word, Nearest neighbor classification, Bayesian classification

Ex 11 - Condensation Tracker

CONDENSATION algorithm, particle filter, tracking

Review checklist

Topic 1 - MVG

• Basic geometry and algebra
• Camera model
• Structure from motion
• Multiview stereo

Topic 2 - Features

• Harris corner
• SIFT
• Feature matching strategy

Topic 3 - State estimation and tracking

• Kalman filter
• Particle filter
• Optical flow

Topic 4 - Segmentation

• EM
• Meanshift
• Graph cut based
• Deep learning based

Topic 5 - Detection

• Template matching
• Sliding window and proposal
• Deep learning based

Topic 6 - Classification

• Classifiers
• Bag of word
• Deep learning based