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Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning

Bhowmick, Brojeshwar and Patra, Suvam and Chatterjee, Avishek and Govindu, Venu Madhav and Banerjee, Subhashis (2015) Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning. In: 12th Asian Conference on Computer Vision (ACCV), NOV 01-05, 2014, Singapore, SINGAPORE, pp. 273-287.

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Official URL: http://dx.doi.org/10.1007/978-3-319-16808-1_19

Abstract

Despite significant advances in recent years, structure-from-motion (SfM) pipelines suffer from two important drawbacks. Apart from requiring significant computational power to solve the large-scale computations involved, such pipelines sometimes fail to correctly reconstruct when the accumulated error in incremental reconstruction is large or when the number of 3D to 2D correspondences are insufficient. In this paper we present a novel approach to mitigate the above-mentioned drawbacks. Using an image match graph based on matching features we partition the image data set into smaller sets or components which are reconstructed independently. Following such reconstructions we utilise the available epipolar relationships that connect images across components to correctly align the individual reconstructions in a global frame of reference. This results in both a significant speed up of at least one order of magnitude and also mitigates the problems of reconstruction failures with a marginal loss in accuracy. The effectiveness of our approach is demonstrated on some large-scale real world data sets.

Item Type: Conference Proceedings
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Additional Information: Copy right for this article belongs to the SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 05 Nov 2015 08:58
Last Modified: 05 Nov 2015 08:58
URI: http://eprints.iisc.ernet.in/id/eprint/52699

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