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Laxman Ahire, Amit; Basgier, Dennis

AR Tracking with Hybrid, Agnostic And Browser Based Approach

2019

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR 2019). Proceedings

IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) <2, 2019, San Diego, CA>

Mobile platform tools are desirable when it comes to practical augmented reality applications. With the convenience and portability that the form factor has to offer, it lays an ideal basic foundation for a feasible use case in industry and commercial applications. Here, we present a novel approach of using the monocular Simultaneous Localization and Mapping (SLAM) [1], [2] information provided by a Cross-Reality (XR) device [3] to augment the linked 3D CAD models. The main objective is to use the tracking technology for an augmented and mixed reality experience by tracking a 3D model and superimposing its respective 3D CAD model data over the images we receive from the camera feed of the XR device without any scene preparation (e.g markers or feature maps). The intent is to conduct a visual analysis and evaluations based on the intrinsic and extrinsic of the model in the visualization system that instant3Dhub [4] has to offer. To achieve this we make use of the Apple’s ARKit to obtain the images, sensor data and SLAM heuristic of client XR device, remote marker-less model based 3D object tracking from monocular RGB image data and hybrid client server architecture. Our approach is agnostic of any SLAM system or Augmented Reality (AR) framework. We make use of the Apple’s ARKit because of the its ease of use, affordability, stability and maturity as a platform and as an integrated system.