Embedded System for Visual Odometry and Localization of Moving Objects in Images Acquired by Unmanned Aerial Vehicles

Abstract

In this paper is presented the visual odometry and the localization of moving objects from aerial images embedded in an Unmanned Aerial Vehicle system with use of the Raspberry Pi and an IP camera. The techniques used are the Oriented FAST and Rotated BRIEF (ORB) descriptor to detect and extract the interest points and the RANdom SAmple Consensus (RANSAC) method to estimate the parameters from a matched points matrix for finding the camera translation. The visual odometry and morphological operations to point out moving objects have been performed.