Abstract:
In this paper, we propose an algorithm for tracking mobile devices (such as smartphones, tablets, or smartglasses) in a known environment for augmented reality applicatio...Show MoreMetadata
Abstract:
In this paper, we propose an algorithm for tracking mobile devices (such as smartphones, tablets, or smartglasses) in a known environment for augmented reality applications. For this purpose, we interpret the environment as an extended object with a known shape, and design likelihoods for different types of image features, using association models from extended object tracking. Based on these likelihoods, and together with sensor information of the inertial measurement unit of the mobile device, we design a recursive Bayesian tracking algorithm. We present results of our first prototype and discuss the lessons we learned from its implementation. In particular, we set up a “pick-by-vision” scenario, where the location of objects in a shelf is to be highlighted in a camera image. Our experiments confirm that the proposed tracking approach achieves accurate and robust tracking results even in scenarios with fast motion.
Published in: 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
Date of Conference: 19-21 September 2016
Date Added to IEEE Xplore: 13 February 2017
ISBN Information: