The SIFT (Scale Invariant Feature Transform) Detector and Descriptor developed by David Lowe University of British Columbia Initial paper ICCV 1999 Newer.
Object Recognition using Invariant Local Features Applications l Mobile robots, driver assistance l Cell phone location or object recognition l Panoramas,
Fast High-Dimensional Feature Matching for Object Recognition David Lowe Computer Science Department University of British Columbia.
Automatic Image Alignment (feature-based) 15-463: Computational Photography Alexei Efros, CMU, Fall 2005 with a lot of slides stolen from Steve Seitz and.
Image Features: Descriptors and matching CSE 576, Spring 2005 Richard Szeliski.
NIPS 2003 Tutorial Real-time Object Recognition using Invariant Local Image Features David Lowe Computer Science Department University of British Columbia.
05a Feature Creation Selection
CSE 185 Introduction to Computer Vision Local Invariant Features.
CSE 185 Introduction to Computer Vision
Machine Learning Feature Creation and Selection
Review: Matt Brown ’ s Canonical Frames
Jeff Howbert Introduction to Machine Learning Winter 2012 1 Machine Learning Feature Creation and Selection.
