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As shared, collaborative, networked, virtual environments become increasinglypopular, various challenges arise regarding the efficient transmission of modeland scene transformation data over the network. As user immersion and real-timeinteractions heavily depend on VR stream synchronization, transmitting theentire data sat does not seem a suitable approach, especially for sessionsinvolving a large number of users. Session recording is anothermomentum-gaining feature of VR applications that also faces the same challenge.The selection of a suitable data format can reduce the occupied volume, whileit may also allow effective replication of the VR session and optimizedpost-processing for analytics and deep-learning algorithms. In this work, wepropose two algorithms that can be applied in the context of a networkedmultiplayer VR session, to efficiently transmit the displacement andorientation data from the users' hand-based VR HMDs. Moreover, we present anovel method describing effective VR recording of the data exchanged in such asession. Our algorithms, based on the use of dual-quaternions and multivectors,impact the network consumption rate and are highly effective in scenariosinvolving multiple users. By sending less data over the network andinterpolating the in-between frames locally, we manage to obtain better visualresults than current state-of-the-art methods. Lastly, we prove that, forrecording purposes, storing less data and interpolating them on-demand yields adata set quantitatively close to the original one.

Less Is More: Efficient Networked VR Transformation Handling Using Geometric Algebra