Taking the Scenic Route to 3D: Optimising Reconstruction from Moving Cameras

Mendez Maldonado, Oscar, Hadfield, Simon, Pugeault, Nicolas and Bowden, Richard (2017) Taking the Scenic Route to 3D: Optimising Reconstruction from Moving Cameras In: IEEE International Conference on Computer Vision 2017, 22 - 29 October 2017, Venice, Italy.

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Abstract

Reconstruction of 3D environments is a problem that has been widely addressed in the literature. While many approaches exist to perform reconstruction, few of them take an active role in deciding where the next observations should come from. Furthermore, the problem of travelling from the camera’s current position to the next, known as pathplanning, usually focuses on minimising path length. This approach is ill-suited for reconstruction applications, where learning about the environment is more valuable than speed of traversal. We present a novel Scenic Route Planner that selects paths which maximise information gain, both in terms of total map coverage and reconstruction accuracy. We also introduce a new type of collaborative behaviour into the planning stage called opportunistic collaboration, which allows sensors to switch between acting as independent Structure from Motion (SfM) agents or as a variable baseline stereo pair. We show that Scenic Planning enables similar performance to state-of-the-art batch approaches using less than 0.00027% of the possible stereo pairs (3% of the views). Comparison against length-based pathplanning approaches show that our approach produces more complete and more accurate maps with fewer frames. Finally, we demonstrate the Scenic Pathplanner’s ability to generalise to live scenarios by mounting cameras on autonomous ground-based sensor platforms and exploring an environment.

Item Type:	Conference or Workshop Item (Conference Paper)
Divisions :	Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :	Name Email ORCID Mendez Maldonado, Oscar o.mendez@surrey.ac.uk Hadfield, Simon s.hadfield@surrey.ac.uk Pugeault, Nicolas N.Pugeault@surrey.ac.uk Bowden, Richard R.Bowden@surrey.ac.uk
Date :	25 December 2017
DOI :	10.1109/ICCV.2017.501
Copyright Disclaimer :	© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User :	Melanie Hughes
Date Deposited :	25 Jul 2017 12:48
Last Modified :	05 Jul 2018 08:30
URI:	http://epubs.surrey.ac.uk/id/eprint/841750

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