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2016 | OriginalPaper | Chapter

Moving Objects Tracking on the Unit Sphere Using a Multiple-Camera System on a Mobile Robot

Authors : Josip Ćesić, Ivan Marković, Ivan Petrović

Published in: Intelligent Autonomous Systems 13

Publisher: Springer International Publishing

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Abstract

Detection and tracking of moving objects with camera systems mounted on a mobile robot presents a formidable problem since the ego-motion of the robot and the moving objects jointly form a challengingly discernible motion in the image. In this paper, we are concerned with multiple-camera systems, namely the Ladybug\(^{\textregistered }2\) camera, whose perspective images were used to detect motion and subsequently perform the tracking of multiple objects on the sphere. This enabled us to account for the continuity of the scene which is achieved by the sensor in an image stitching process on the sphere. The objects are tracked on the sphere with a Bayesian filter based on the von Mises–Fisher distribution and the data association is achieved by the global nearest neighbor method, for which the distance matrix is constructed by deriving the Rényi \(\alpha \)-divergence for the von Mises–Fisher distribution. The prospects of the method are tested on a synthetic and real-world data experiments.

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previous chapter 3D Object Recognition Using Convolutional Neural Networks with Transfer Learning Between Input Channels
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Metadata
Title
Moving Objects Tracking on the Unit Sphere Using a Multiple-Camera System on a Mobile Robot
Authors
Josip Ćesić
Ivan Marković
Ivan Petrović
Copyright Year
2016
Book
Intelligent Autonomous Systems 13

Print ISBN: 978-3-319-08337-7

Electronic ISBN: 978-3-319-08338-4

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-08338-4_65

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