Visual Odometry is the process of determining the position and orientation of a robot or any other vehicle by analyzing the associated camera images. It has been used in various vehicles like Mars Rovers and self-driving cars. It is a crucial element for robotic mapping and navigation.

Visual Keypoints and Detectors

• FAST : The FAST (Features from Accelerated Segment Test) keypoint detector identifies corners in an image through a clever and efficient method
• oFAST : Oriented FAST (oFAST) keypoint detector
• BRIEF : The BRIEF (Binary Robust Independent Elementary Features) descriptor is a highly efficient feature descriptor that converts an image patch around a keypoint into a compact binary string. This process makes it fast to compute and compare, suitable for real-time applications.

Matching

• FLANN : Fast Library for Approximate Nearest Neighbors (FLANN) is a library that focuses on the problem of finding "nearest neighbors" in large datasets, a fundamental operation in many machine learning, computer vision, and pattern recognition tasks.
• k-d trees : K-d trees, short for "k-dimensional trees," are a data structure used for organizing points in a k-dimensional space. K-d trees are particularly useful for various applications, such as searches involving multidimensional keys (like range searches and nearest neighbor searches) and are commonly used in fields such as computer graphics, machine learning, and spatial database search.