Conference Proceedings

MODELLING UNCERTAINTY of SINGLE IMAGE INDOOR LOCALISATION USING A 3D MODEL and DEEP LEARNING

D Acharya, S Singha Roy, K Khoshelham, S Winter

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences | Published : 2019

Abstract

Abstract. Many current indoor localisation approaches need an initial location at the beginning of localisation. The existing visual approaches to indoor localisation perform a 3D reconstruction of the indoor spaces beforehand, for determining this initial location, which is challenging for large indoor spaces. In this research, we present a visual approach for indoor localisation that is eliminating the requirement of any image-based reconstruction of indoor spaces by using a 3D model. A deep Bayesian convolutional neural network is fine-tuned with synthetic images generated from a 3D model to estimate the camera pose of real images. The uncertainty of the estimated camera poses is modelled..

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