Computer vision is one of the most active research fields in information technology today.
Giving machines and robots the ability to see and comprehend the surrounding world at the …

Feature detection and description algorithms represent an important milestone in most
computer vision applications. They have been examined from various perspectives during …

The computer vision system is the technology that deals with identifying and detecting the
objects of a particular class in digital images and videos. Local feature detection and …

This book provides readers with a selection of high-quality chapters that cover both
theoretical concepts and practical applications of image feature detectors and descriptors. It …

Several visual feature extraction algorithms have recently appeared in the literature, with the
goal of reducing the computational complexity of state-of-the-art solutions (eg, SIFT and …

This chapter introduces the reader to the various aspects of feature extraction covered in this
book. Section 1 reviews definitions and notations and proposes a unified view of the feature …

Performance evaluation of salient features has a long-standing tradition in computer vision.
In this paper, we fill the gap of evaluation for the recent wave of binary feature descriptors …

A novel search principle for optimal feature subset selection using the branch & bound
method is introduced. Thanks to a simple mechanism for predicting criterion values, a …

The goal of feature selection is to find the optimal subset consisting of m features chosen
from the total n features. One critical problem for many feature selection methods is that an …

There has been significant research into the development of visual feature detectors and
descriptors that are robust to a number of image deformations. Some of these methods have …