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Abstract:Tracking the 6DoF pose of arbitrary 3D objects is a fundamental topic in Augmented Reality (AR) research, having received a large amount of interest in the last decades. The necessity of accurate and computationally efficient object tracking is evident for a broad base of today's AR applications. In this work we present a fully comprehensive pipeline for 6DoF Object Tracking based on 3D scans of objects, covering object registration, initialization and frame to frame tracking, implemented to optimize the user experience and to perform well in all typical challenging conditions such as fast motion, occlusions and illumination changes. Furthermore, we present the deployment of our tracking system in a Remote Live Support AR application with 3D object-aware registration of annotations and remote execution for delay and performance optimization. Experimental results demonstrate the tracking quality, real-time capability and the advantages of remote execution for computationally less powerful mobile devices.

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In this paper, we are choosing a suitable indoor-outdoor propagation model out of the existing models by considering path loss and distance as parameters. A path loss is calculated empirically by placing emitter nodes inside a building. A receiver placed outdoors is represented by a Quadrocopter (QC) that receives beacon messages from indoor nodes. As per our analysis, the International Telecommunication Union (ITU) model, Stanford University Interim (SUI) model, COST-231 Hata model, Green-Obaidat model, Free Space model, Log-Distance Path Loss model and Electronic Communication Committee 33 (ECC-33) models are chosen and evaluated using empirical data collected in a real environment. The aim is to determine if the analytically chosen models fit our scenario by estimating the minimal standard deviation from the empirical data.