HOG Descriptor in MATLAB
To help in my understanding of the HOG descriptor, as well as to allow me to easily test out modifications to the descriptor, I wrote functions in Octave / Matlab for computing the HOG descriptor for a detection window.
HOG Person Detector Tutorial
One of the most popular and successful “person detectors” out there right now is the HOG with SVM approach. When I attended the Embedded Vision Summit in April 2013, it was the most common algorithm I heard associated with person detection.
Gradient Vectors
Gradient vectors (or “image gradients”) are one of the most fundamental concepts in computer vision; many vision algorithms involve computing gradient vectors for each pixel in an image.
SVM Tutorial - Part I
I found it really hard to get a basic understanding of Support Vector Machines. To learn how SVMs work, I ultimately went through Andrew Ng’s Machine Learning course (available freely from Stanford). I think the reason SVM tutorials are so challenging is that training an SVM is a complex optimization problem, which requires a lot of math and theory to explain.
Stanford Machine Learning - Lecture 6
This lecture covers: