https://www.auroraviewer.org/home daily 1.0 2022-04-25 https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/9e7ff9e2-4284-41c2-9ec2-2cd27804789c/Aurora_visual_positioning_service-01.png Home - Open Source Visual Positional Service By George mason University https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/8a9c12dd-6a68-47a2-8deb-7014ca4e6cc4/Aurora+Image+thumbnail+Landing+page-01.png Home - AURORA view Unity Reference Client https://www.auroraviewer.org/opensource-visual-positioning-service daily 0.75 2022-04-25 https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/75b32931-017c-4210-bdc8-19246f0cd76a/OpenSource_reconstruction+tool.png Open Source Visual Positioning Service - Open Source Visual Positioning Service by George Mason University Under the lead of Bo Han, the team at George Mason University (GMU) is developing an open-source visual positioning service (VPS). A spatial map consists of sparse 3D points (i.e., a point cloud) with visual feature descriptors, to store explicit geometric information and semantic knowledge of the surrounding environment in volumetric views. Widely used methods for spatial mapping include structure from motion (SfM) and visual SLAM (simultaneous localization and mapping), which processes images that capture the physical world. During localization, a mobile device extracts its camera image and uploads them to a server that matches them with the 3D features in the spatial map to estimate the device’s 6DoF pose. This method is referred to as image-based localization. In order to protect user privacy, the device can also extract 2D features from the camera image for uploading, instead of directly sending the image. The GMU team is building the backend service of a VPS by leveraging existing open-source packages for structure from motion and hierarchical visual localization, including Colmap (https://github.com/colmap/colmap) and Hierarchical Localization (HLOC) (https://github.com/cvg/Hierarchical-Localization). The team has built the mapping and localization service's back-end service by leveraging Colmap. https://www.auroraviewer.org/location daily 0.75 2022-04-25 https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/75c3ad8a-1ebd-4bcd-96ef-0c0f4b2f01d3/Experiment_03.png Testing - Make it stand out 3D reconstruction of the laboratory with open-source reconstruction tools, using as input the capture dataset we collected with our app. The coloured dots are the feature points of the room, and the red rectangles represent the individual images (captured in panorama circles). https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/ef295405-8968-4a3c-9f8f-128ea20dd99f/Experiment_02_01.png Testing - Make it stand out Overview of the interaction flow in our live IoT data visualization scenario https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/ef92a79e-fdc2-4821-9d86-4e22841096ad/Experiment_01_02.png Testing - Make it stand out Sparcl (WebXR client) in the WINLAB, discovering the available service, discovering the existing contents, and discovering the newly created fox. https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/de95b5ad-8fae-4e2a-8b45-e638e652b62c/Experiment_01.png Testing - Make it stand out AuroraViewer (Unity client) in WINLAB, discovering services, discovering the existing contents, and creating a new fox. https://www.auroraviewer.org/auroraviewer daily 0.75 2022-04-25 https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/f9dc4961-d156-44f5-be58-fe7f129c0dea/Unity+reference+client.png Aurora Viewer - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://www.auroraviewer.org/about daily 0.75 2022-04-07 https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/2f5b3a81-5e1d-4063-9130-34ab1a9d2875/Spatial_Computing+Platform.png About Spatial computing relies on a number of fundamental technologies such as real-world 3D capture (sparse and dense point cloud mapping), precise localization with six degrees of freedom, and discovery and delivery of personalized content to users. Today, these building blocks are only available from and controlled by a few major companies (Microsoft, Apple, Google, Meta, etc) in siloed platforms. The Open AR Cloud (OARC) association is dedicated to the development of technologies and standards for open and interoperable spatial computing components on which an ecosystem of companies and their services can flourish. The OARC has already designed and implemented prototypes of important building blocks of an Open Spatial Computing Platform (OSCP), shown in Figure 2. The OARC has released the components as open-source code (see https://github.com/OpenArCloud) and these are already deployed in an OARC testbed in Bari, Italy. The existing OARC testbed has proven that the OSCP enables discovery of spatial services, localization of users based on images sent from the user’s mobile camera, discovery of digital multimedia content attached to physical locations or smart objects and sensors, and display of content to test bed-connected users. Based on personalized user preferences, location, and other context information, the retrieved content can be dynamically filtered. With support of the NGI Atlantic program, the Open AR Cloud (OARC) Europe team is adapting the reference implementation of the OSCP and deploying the components on the COSMOS 5G platform in Manhattan. In addition, the team creates a new Unity-based reference client application and two representative demo applications. The team is also working on integrating a new, open-source Visual Positioning Service developed by George Mason University. The COSMOS 5G deployment of the OSCP will allow conducting experiments that will deepen understanding of limitations and opportunities of the OSCP, provide component and network performance metrics, and trigger development of new software to increase the capabilities and features of the OSCP. The integration with an open-source VPS will permit any provider https://images.squarespace-cdn.com/content/v1/62277b319aecd968340fea90/9fa07a1c-355a-49f5-b54a-82aa62cc3133/Spatial+computing_image.png About Project Vision Spatial computing is a broad term for a suite of technologies that result in users being immersed, engaged, and interacting with spatial and temporal digital information that pertains to the physical space in, around, and near the user. It consists of a superset of technologies required for traditional Augmented Reality. Figure 1 introduces the concept and the most important terminology.