Computer Vision
Course Feature
Class Description
Course ID: D5
Unit: DATA SCIENCE AND ENGINEERING – Unit D: Data Analysis and Processing
Weekly Hours: 4
Type:
ECTS Credits: 7
Course Homepage:
Description:• Linear filtering • Edge detection • Frequency representation, image pyramids, template matching • Local features: corners • Local features: scale and interest point descriptors • Machine learning for computer vision • Segmentation by clustering: mean shift • Segmentation by clustering: normalized cut • Segmentation by fitting a model: Hough transform and least squares fitting • Segmentation by fitting a model: robust estimators and RANSAC • Registration • PCA and eigenfaces • Face detection • Fitting probability models • Learning and inference in computer vision • The pinhole camera • Singular value decomposition • Models for transformations • Multiple cameras • More features (LBP, shape context, dual PCA) • Models for grids (grpah cut) • Regression • Classification