Vision-based Localization Using by Line with Point for Feature loss

Kyu-Hyun Sung, S. Manzoor, HyunJi Park, Tae-Yong Kuc
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Abstract

This paper presents a solution to overcome the shortcomings of point feature localization, and estimates the pose using points and lines. Vision-based localization estimates the position and orientation from camera information. It is used in unmanned driving systems, AR (Augmented Reality), and VR (Virtual Reality) to recognize the surrounding environment. Real-time performance is a challenging task for these systems to accomplish the missions based on the determined position. In this situation, ORB feature point extraction method is used. However, ORB feature extraction is based on points, position estimation cannot be performed if the feature cannot be extracted. In this paper, we handle this issue using our proposed architecture by extracting the line and using the number of missing features to estimate the camera’s orientation. We also created an experimental environment in the actual world and confirmed the validity of the presented algorithm.
基于点与线的特征丢失视觉定位
针对点特征定位的不足,提出了一种基于点和线的姿态估计方法。基于视觉的定位是根据相机信息估计位置和方向。它被用于无人驾驶系统、AR(增强现实)和VR(虚拟现实),以识别周围环境。实时性能对这些系统来说是一项具有挑战性的任务,因为它们需要完成基于确定位置的任务。在这种情况下,采用ORB特征点提取方法。但是ORB特征提取是基于点的,如果提取不到特征,就无法进行位置估计。在本文中,我们使用我们提出的架构来处理这个问题,通过提取线和使用缺失特征的数量来估计相机的方向。我们还在现实世界中创建了一个实验环境,验证了所提出算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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