基於影像的自我定位

Abstract

本論文提出了一種基於影像的定位系統架構,在精度和速度上獲得 提高,并壓縮比較資料庫的大小,使其適用于聯網設備在已知場景內 的自我定位。現有的消費型 GPS 設備的精確度都在數公尺級別,在衛 星連接環境不理想的情況下可能誤差更高甚至無法提供定位。而目前 基於影像定位的研究使用的各種方法,均在精度,速度或是比較資料 庫大小上遇到障礙,限制其在一些問題上的應用。我們通過不同場景的 實驗,表明了本文提出的方法可以在保持低於一公尺的誤差的前提下 有效壓縮比較資料庫的大小。在評估效果的同時,本文分析了影響定 位精度的多種因素,亦探討所遇到的問題及其解決方案,以求進一步 的提升和運用。

This thesis proposes an image-based ego-positioning framework to achieve sub-meter accuracy, with compact reference database compared to previous work, which can be used for the positioning of Internet connected devices. Consumer GPS devices nowadays obtain accuracy around several meters, which could be worse or even unable to work depending on the connection with GPS satellites. Current researches on image-based positioning utilize images and the reference database in different ways, however their accuracy, time consumption or database size have set limitations of their application. Experiments on different scenes in this work demonstrate that the method we proposed effectively reduce the size of reference database while main- taining a sub-meter accuracy for positioning. With evaluated performance, influencing factors are investigated, open problems are discussed for further improvements and applications.