A panoramic walkthrough system with occlusion culling

Occlusion Culling for Wide-Angle Computer-Generated Holograms Using Phase Added Stereogram Technique

Photonics ◽

10.3390/photonics8080298 ◽

2021 ◽

Vol 8 (8) ◽

pp. 298

Author(s):

Juan Martinez-Carranza ◽

Tomasz Kozacki ◽

Rafał Kukołowicz ◽

Maksymilian Chlipala ◽

Moncy Sajeev Idicula

Keyword(s):

Point Sources ◽

Wide Angle ◽

Computer Generated Holograms ◽

Propagation Methods ◽

Propagation Technique ◽

3D Scene ◽

Occlusion Culling ◽

Fourier Type ◽

Cloud Of Points

A computer-generated hologram (CGH) allows synthetizing view of 3D scene of real or virtual objects. Additionally, CGH with wide-angle view offers the possibility of having a 3D experience for large objects. An important feature to consider in the calculation of CGHs is occlusion between surfaces because it provides correct perception of encoded 3D scenes. Although there is a vast family of occlusion culling algorithms, none of these, at the best of our knowledge, consider occlusion when calculating CGHs with wide-angle view. For that reason, in this work we propose an occlusion culling algorithm for wide-angle CGHs that uses the Fourier-type phase added stereogram (PAS). It is shown that segmentation properties of the PAS can be used for setting efficient conditions for occlusion culling of hidden areas. The method is efficient because it enables processing of dense cloud of points. The investigated case has 24 million of point sources. Moreover, quality of the occluded wide-angle CGHs is tested by two propagation methods. The first propagation technique quantifies quality of point reproduction of calculated CGH, while the second method enables the quality assessment of the occlusion culling operation over an object of complex shape. Finally, the applicability of proposed occlusion PAS algorithm is tested by synthetizing wide-angle CGHs that are numerically and optically reconstructed.

Download Full-text

Depth estimation with cascade occlusion culling filter for light-field cameras

2016 23rd International Conference on Pattern Recognition (ICPR) ◽

10.1109/icpr.2016.7899912 ◽

2016 ◽

Author(s):

Wenhui Zhou ◽

Andrew Lumsdaine ◽

Lili Lin

Keyword(s):

Light Field ◽

Depth Estimation ◽

Occlusion Culling

Download Full-text

A POINT-BASED ASYNCHRONOUS REMOTE VISUALIZATION FRAMEWORK FOR REAL-TIME VIRTUAL REALITY

International Journal of Image and Graphics ◽

10.1142/s0219467808003040 ◽

2008 ◽

Vol 08 (02) ◽

pp. 189-207

Author(s):

JINGHUA GE ◽

DANIEL J. SANDIN ◽

TOM PETERKA ◽

ROBERT KOOIMA ◽

JAVIER I. GIRADO ◽

...

Keyword(s):

Virtual Reality ◽

Real Time ◽

High Speed ◽

Large Scale ◽

Julia Set ◽

Remote Visualization ◽

Space Partition ◽

Original Dataset ◽

View Reconstruction ◽

Occlusion Culling

High speed interactive virtual reality (VR) exploration of scientific datasets is a challenge when the visualization is computationally expensive. This paper presents a point-based remote visualization pipeline for real-time virtual reality (VR) with asynchronous client-server coupling. Steered by the client-end frustum request, the remote server samples the original dataset into 3D point samples and sends them back to the client for view updating. From every view updating frame, the client incrementally builds up a point-based geometry under an octree-based space partition hierarchy. At every view-reconstruction frame, the client continuously splats the available points onto the screen with efficient occlusion culling and view-dependent level of detail (LOD) control. An experimental visualization framework with a server-end computer cluster and a client-end head-tracked autostereo VR desktop display is used to visualize large-scale mesh datasets and ray-traced 4D Julia set datasets. The overall performance of the VR view reconstruction is about 15 fps and independent of the original dataset complexity.

Download Full-text