Image and video descriptors
Abdenour Hadid · 2010
Feature (or descriptor) extraction from images and videos is a very crucial task in almost all computer vision systems. It consists of extracting characteristics describing important information in the images and videos. Different global (or holistic) methods such as Principal Component Analysis (PCA) have been widely studied and applied but lately local descriptors (such as LBP, SIFT and Gabor) have gained more attention due to their robustness to challenges such as pose and illumination changes. This tutorial gives an exhaustive overview of different image and video descriptors which can be found in literature with an emphasis on the most recent developments in the field. The tutorial will then focus on one or two state-of-the-art descriptors to demonstrate step by step how to successfully apply them to various computer vision problems such as biometrics, texture analysis, image and video retrieval, motion and activity analysis, human-computer interaction etc.