Zhou Yan, Zheng Xianwei, Chen Ruizhi, Xiong Hanjiang, Guo Sheng
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China.
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China.
Sensors (Basel). 2018 Jan 17;18(1):258. doi: 10.3390/s18010258.
Accurately determining pedestrian location in indoor environments using consumer smartphones is a significant step in the development of ubiquitous localization services. Many different map-matching methods have been combined with pedestrian dead reckoning (PDR) to achieve low-cost and bias-free pedestrian tracking. However, this works only in areas with dense map constraints and the error accumulates in open areas. In order to achieve reliable localization without map constraints, an improved image-based localization aided pedestrian trajectory estimation method is proposed in this paper. The image-based localization recovers the pose of the camera from the 2D-3D correspondences between the 2D image positions and the 3D points of the scene model, previously reconstructed by a structure-from-motion (SfM) pipeline. This enables us to determine the initial location and eliminate the accumulative error of PDR when an image is successfully registered. However, the image is not always registered since the traditional 2D-to-3D matching rejects more and more correct matches when the scene becomes large. We thus adopt a robust image registration strategy that recovers initially unregistered images by integrating 3D-to-2D search. In the process, the visibility and co-visibility information is adopted to improve the efficiency when searching for the correspondences from both sides. The performance of the proposed method was evaluated through several experiments and the results demonstrate that it can offer highly acceptable pedestrian localization results in long-term tracking, with an error of only 0.56 m, without the need for dedicated infrastructures.
利用消费级智能手机在室内环境中准确确定行人位置是泛在定位服务发展中的重要一步。许多不同的地图匹配方法已与行人航位推算（PDR）相结合，以实现低成本且无偏差的行人跟踪。然而，这仅在具有密集地图约束的区域有效，且误差会在开放区域累积。为了在无地图约束的情况下实现可靠定位，本文提出了一种改进的基于图像的定位辅助行人轨迹估计方法。基于图像的定位从二维图像位置与场景模型的三维点之间的二维 - 三维对应关系中恢复相机姿态，该场景模型先前由运动结构（SfM）管道重建。这使我们能够在成功配准图像时确定初始位置并消除PDR的累积误差。然而，由于当场景变大时传统的二维到三维匹配会拒绝越来越多的正确匹配，图像并非总能配准。因此，我们采用一种鲁棒的图像配准策略，通过整合三维到二维搜索来恢复最初未配准的图像。在此过程中，采用可见性和共同可见性信息来提高从两侧搜索对应关系时的效率。通过多个实验对所提方法的性能进行了评估，结果表明该方法在长期跟踪中能提供高度可接受的行人定位结果，误差仅为0.56米，且无需专用基础设施。
