Marker-Less Augmented Reality Framework Using On-Site 3D Line-Segment-based Model Generation
The authors propose a line-segment-based marker-less augmented reality (AR) framework that involves an on-site model-generation method and on-line camera tracking. In most conventional model-based marker-less AR frameworks, correspondences between the 3D model and the 2D frame for camera-pose estimation are obtained by feature-point matching. However, 3D models of the target scene are not always available, and feature points are not detected from texture-less objects. The authors’ framework is based on a model-generation method with an RGB-D camera and model-based tracking using line segments, which can be detected even with only a few feature points. The camera pose of the input images can be estimated from the 2D‐3D line-segment correspondences given by a line-segment feature descriptor. The experimental results show that the proposed framework can achieve AR when other point-based frameworks cannot. The authors also argue that their framework can generate a model and estimate camera pose more accurately than their previous study.
Document Type: Research Article
Publication date: March 1, 2016
This article was made available online on December 18, 2015 as a Fast Track article with title: "Marker-Less Augmented Reality Framework Using On-Site 3D Line-Segment-based Model Generation".
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