Presentation

<
33. Temporal Hierarchical Gaussian Mixture Models for Real-Time Point Cloud Streaming
SessionPosters: Geometry & Modeling
DescriptionWe propose a novel approach for point cloud streaming consisting of a methodology that constructs a hierarchy of GMMs. This allows for a compact footprint and dynamic, progressive transmission and rendering of LODs. We achieve real-time and high-fidelity reconstructions by exploiting temporal coherence and a highly parallelized CUDA implementation.
Contributors
Roland Fischer
University of Bremen
Tobias Gels
University of Bremen
Rene Weller
University of Bremen
Gabriel Zachmann
University of Bremen
Event Type
Poster
TimeSunday, 28 July 20249:00am - 5:30pm MDT
LocationMile High Pre-Function Area
Session TimeSunday, 28 July 20249:00am - 5:30pm MDTMonday, 29 July 20249:00am - 5:30pm MDTTuesday, 30 July 20249:00am - 5:30pm MDTWednesday, 31 July 20249:00am - 5:30pm MDTThursday, 1 August 20249:00am - 5:30pm MDT
LocationMile High Pre-Function Area
Registration Categories
Full Conference
Full Conference Supporter
Experience
Exhibitor Full Conference
Exhibitor Experience
Next PresentationNext Presentation19. A Real-time Visualization System of Pseudo-muscle Activity Using a VR Device