Abstract
Smartphone indoor positioning ground truth is difficult to directly, dynamically, and precisely measure in real-time. To solve this problem, this paper proposes and implements a robust smartphone high-precision indoor positioning dynamic real-time ground truth reference system using color visual scatter-encoded targets based on machine vision and photogrammetry. First, a kind of novel high-precision color vision scatter-encoded patterns with a robust recognition rate is designed. Then we use a smartphone to obtain a sequence of images of an experimental room and extract the base points of the color visual scatter-encoded patterns from the sequence images to establish the indoor local coordinate system of the encoded targets. Finally, we use a high-efficiency algorithm to decode the targets of a real-time dynamic shooting image to obtain accurate instantaneous pose information of a smartphone camera and establish the high-precision and high-availability smartphone indoor positioning direct ground truth reference system for preliminary real-time accuracy evaluation of other smartphone positioning technologies. The experimental results show that the encoded targets of the color visual scatter-encoded pattern designed in this paper are easy to detect and identify, and the layout is simple and affordable. It can accurately and quickly solve the dynamic instantaneous pose of a smartphone camera to complete the self-positioning of the smartphone according to the artificial scatter feature visual positioning technology. It is a fast, efficient and low-cost accuracy-evaluation method for smartphone indoor positioning.
Funder
Ministry of science and technology of China
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
9 articles.
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