Robust Real-Time Visual Odometry Estimation for 3D Scene Reconstruction


KIPS Transactions on Software and Data Engineering, Vol. 4, No. 4, pp. 187-194, Apr. 2015
10.3745/KTSDE.2015.4.4.187, Full Text:

Abstract

In this paper, we present an effective visual odometry estimation system to track the real-time pose of a camera moving in 3D space. In order to meet the real-time requirement as well as to make full use of rich information from color and depth images, our system adopts a feature-based sparse odometry estimation method. After matching features extracted from across image frames, it repeats both the additional inlier set refinement and the motion refinement to get more accurate estimate of camera odometry. Moreover, even when the remaining inlier set is not sufficient, our system computes the final odometry estimate in proportion to the size of the inlier set, which improves the tracking success rate greatly. Through experiments with TUM benchmark datasets and implementation of the 3D scene reconstruction application, we confirmed the high performance of the proposed visual odometry estimation method.


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Cite this article
[IEEE Style]
J. H. Kim and I. C. Kim, "Robust Real-Time Visual Odometry Estimation for 3D Scene Reconstruction," KIPS Transactions on Software and Data Engineering, vol. 4, no. 4, pp. 187-194, 2015. DOI: 10.3745/KTSDE.2015.4.4.187.

[ACM Style]
Joo Hee Kim and In Cheol Kim. 2015. Robust Real-Time Visual Odometry Estimation for 3D Scene Reconstruction. KIPS Transactions on Software and Data Engineering, 4, 4, (2015), 187-194. DOI: 10.3745/KTSDE.2015.4.4.187.