CUED Publications database

SKen: A statistical test for removing outliers in optical flow: A 3D reconstruction case

Macedo, S and Vasconcelos, L and Cesar, V and Pessoa, S and Kelner, J (2014) SKen: A statistical test for removing outliers in optical flow: A 3D reconstruction case. In: UNSPECIFIED pp. 202-209..

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Abstract

The 3D reconstruction can be employed in several areas such as markerless augmented reality, manipulation of interactive virtual objects and to deal with the occlusion of virtual objects by real ones. However, many improvements into the 3D reconstruction pipeline in order to increase its efficiency may still be done. In such context, this paper proposes a filter for optimizing a 3D reconstruction pipeline. It is presented the SKen technique, a statistical hypothesis test that classifies the features by checking the smoothness of its trajectory. Although it was not mathematically proven that inliers features performed smooth camera paths, this work shows some evidence of a relationship between smoothness and inliers. By removing features that did not present smooth paths, the quality of the 3D reconstruction was enhanced. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Subjects: UNSPECIFIED
Divisions: Div C > Engineering Design
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:44
Last Modified: 31 Oct 2017 01:43
DOI: