Spatio-temporal reasoning in mixed reality with a hybrid approach to support scalability and development of virtuality-reality continnum software

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Recent advances in technology have led to the introduction of a new class of computing devices that combine computer-generated information with the "physical" world in a reality-virtuality continuum, such as Mixed Reality (MR). MR relies on contextual information to integrate virtual content within the physical environment and recognize users' actions to foster intuitive and natural interactions. In this project, we work on a first challenge in MR which resides in improving spatiotemporal reasoning by recognizing objects in a 3D world and tracking them while the users interact in a reality-virtuality continuum. As a second challenge, we will work in supporting the knowledge transfers and the construction of a common representation of an environment in MR between several users and several local or remote physical spaces. The expected results of the project will consist in algorithms and models for MR that will be implemented in two MR based context-aware decision support application prototypes for the Industry 4.0 and healthcare, as well as experimental results collected during in labs and on the field tests with potential users in Industry 4.0 and healthcare. The industry partner in this project is VMware Canada, a leader in intelligent multi-cloud ecosystems. It is expected that the use case of Mixed Reality, which is considered in this project, will play a pivotal role in the next generation - namely 6G - of mobile networks, which is one of the key research areas for the VMWare Distributed Edge (DE). The research conducted in this project to enhance Mixed Reality experiences, its scability and its demonstration (in Industry 4.0 and in healthcare) in a jointly identified infrastructure is therefore of utmost interest for VMware.