GRIHA: Synthesizing 2-Dimensional Building Layouts from Images Captured using a Smart Phone
This addresses the need for accessible and efficient indoor layout generation for users without specialized hardware, though it is incremental as it builds on existing SLAM technology.
The paper tackles the problem of reconstructing indoor scenes and generating 2D building layouts from images, proposing GRIHA, a framework that uses RGB images from a smartphone camera instead of requiring depth cameras or occlusion-free panoramic photos, and it achieves superior results compared to existing methods.
Reconstructing an indoor scene and generating a layout/floor plan in 3D or 2D is a widely known problem. Quite a few algorithms have been proposed in the literature recently. However, most existing methods either use RGB-D images, thus requiring a depth camera, or depending on panoramic photos, assuming that there is little to no occlusion in the rooms. In this work, we proposed GRIHA (Generating Room Interior of a House using ARCore), a framework for generating a layout using an RGB image captured using a simple mobile phone camera. We take advantage of Simultaneous Localization and Mapping (SLAM) to assess the 3D transformations required for layout generation. SLAM technology is built-in in recent mobile libraries such as ARCore by Google. Hence, the proposed method is fast and efficient. It gives the user freedom to generate 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. Also, the system is tested on multiple hardware platforms to test the dependency and efficiency.