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.
HOG stands for Histograms of Oriented Gradients. HOG is a type of “feature descriptor”. The intent of a feature descriptor is to generalize the object in such a way that the same object (in this case a person) produces as close as possible to the same feature descriptor when viewed under different conditions. This makes the classification task easier.
The creators of this approach trained a Support Vector Machine (a type of machine learning algorithm for classification), or “SVM”, to recognize HOG descriptors of people.
The HOG person detector is fairly simple to understand (compared to SIFT object recognition, for example). One of the main reasons for this is…
View original post 1,485 more words