RABBIT: Live Transcoding of V-PCC Point Cloud Streams

Rudolph, Michael; Schneegaß, Stefan; Rizk, Amr

doi:10.1145/3587819.3590978

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2024

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Cited by 3 publications

References 33 publications

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Volumetric Video on the Web: a platform prototype and empirical study

Cabrero Barros,

Elosegi,

Tamayo

et al. 2024

Proceedings of the 29th International ACM Conference on 3D Web Technology

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Volumetric Video on the Web: a platform prototype and empirical study

Cabrero Barros,

Elosegi,

Tamayo

et al. 2024

Proceedings of the 29th International ACM Conference on 3D Web Technology

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A Clustering Approach to Unveil User Similarities in 6-DoF Extended Reality Applications

Rossi,

Viola,

Toni

et al. 2024

ACM Trans. Multimedia Comput. Commun. Appl.

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The advent in our daily life of Extended Reality (XR) technologies, such as Virtual and Augmented Reality, has led to the rise of user-centric systems, offering higher level of interaction and presence in virtual environments. In this context, understanding the actual interactivity of users is still an open challenge and a key step to enabling user-centric system. In this work, our goal is to construct an efficient clustering tool for 6 Degree-of-Freedom (DoF) navigation trajectories by extending the applicability of existing behavioural tool. Specifically, we first compare the navigation in 6-DoF with its 3-DoF counterpart, highlighting the main differences and novelties. Then, we investigate new metrics aimed at better modelling behavioural similarities between users in a 6-DoF system. More concretely, we define and compare 11 similarity metrics which are based on different distance features ( i.e. , user positions in the 3D space, user viewing directions) and distance measurements ( i.e. , Euclidean, Geodesic, angular distance). Our solutions are validated and tested on real navigation paths of users interacting with dynamic volumetric media in both 6-DoF Virtual Reality and Augmented Reality conditions. Results show that metrics based on both user position and viewing direction better perform in detecting user similarity while navigating in a 6-DoF system. Such easy-to-use but robust metrics allow us to answer a fundamental question for user-centric systems: “how do we detect if users look at the same content in 6-DoF?”, opening the gate to new solutions based on users interactivity, such as viewport prediction, live streaming services optimised based on users behaviour but also for user-based quality assessment methods.

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