GRIHA: synthesizing 2-dimensional building layouts from images captured using a smart phone

Abstract

Indoor scene reconstruction and generating a 2D/3D floor plan is a widely explored problem. In the recent years a few algorithms have been proposed, which either use RGB-D images, requiring a depth capturing camera or depend upon panoramic images, assuming little to no occlusion in the room. In this work, we propose a framework named GRIHA (Generating Room Interior of a House using ARcore), which takes advantage of RGB images taken from a conventional mobile phone camera. The proposed work uses Simultaneous Localization And Mapping (SLAM) technology to estimate the 3D transformations required for layout generation. GRIHA uses SLAM based Google ARcore library for camera pose estimation while capturing the images. It gives the user freedom to generate a layout by merely taking a few conventional photos, rather than relying on specialized depth hardware or occlusion-free panoramic images. We have compared GRIHA with other existing methods and obtained superior results. Moreover, the system is tested on multiple hardware platforms to test the dependency and efficiency.