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1
Intro
2
Corner Detection by Auto-correlation
3
Corner Detection: Mathematics The quadratic approximation simplifies to
4
Histogram of Oriented Gradients
5
Scale Invariant Feature Transform (SIFT)
6
Overall Procedure at a High Level
7
Automatic Scale Selection . Function responses for increasing scale (scale signature)
8
What Is A Useful Signature Function f?
9
Alternative kernel
10
Find local maxima in position-scale space of Dog
11
SIFT Orientation estimation
12
SIFT Orientation Normalization
13
SIFT descriptor formation
14
SIFT Descriptor Extraction
15
Review: Local Descriptors
Description:
Explore advanced computer vision concepts in this 31-minute lecture from the University of Central Florida's CAP5415 course. Dive into corner detection techniques using auto-correlation and mathematical approaches. Learn about the Histogram of Oriented Gradients (HOG) and gain a comprehensive understanding of the Scale Invariant Feature Transform (SIFT) algorithm. Discover the intricacies of automatic scale selection, orientation estimation, and descriptor formation in SIFT. Examine alternative kernels and local maxima detection in position-scale space. Conclude with a review of local descriptors, enhancing your knowledge of feature extraction and image analysis techniques.

Computer Vision Features - Part 2 - Lecture 9

University of Central Florida
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