Single-Image Camera Calibration for Furniture Layout Using Natural-Marker-Based Augmented Reality
Kazumoto Tanaka, Yunchuan ZHANG · IEICE Transactions on Information and Systems · 2022
We propose an augmented-reality-based method for arranging furniture using natural markers extracted from the edges of the walls of rooms. The proposed method extracts natural markers and estimates the camera parameters from single images of rooms using deep neural networks. Experimental results show that in all the measurements, the superimposition error of the proposed method was lower than that of general marker-based methods that use practical-sized markers.