Screen space point sampled shadows

Cowan, Brent; Khattak, Saad; Kapralos, Bill; Hogue, Andrew

doi:10.1109/gem.2015.7377248

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…Percentage Closer Soft Shadows applies a percentage closer filter to shadow maps to improve the quality [65], however, the PCSS algorithm does not correctly handle self-shadowing [101], or shadows from fine filaments such as hair [111]. Screen space shadows [52] processed a shadow map, then raymarched a line from each point on an object's surface where a shadow could be cast, to the light source. The area was rejected if the ray was occluded.…”

Section: Rendering Vector Data Onto Terrainmentioning

confidence: 99%

Immersive visualization for ecosystem services analysis and trade-offs

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<p><strong>Changing land use to improve one ecosystem service can affect other ecosystem services, so a potential land use change should be analysed before implementation. Land use analysts using existing ecosystem services modelling software, and users of the results of ecosystem services analysis identified problems with modelling tools applied to ecosystem services analysis. A User Centred Design process was adopted in this study, to design and implement an immersive Virtual Reality (VR) visualization system, Immersive ESS Visualizer. Immersive ESS Visualizer was designed, and implemented for users of differing levels of geospatial expertise, to assist with visualization and analysis of ecosystem services data. Features include multiple handheld maps, a scenario map, layers, filters, zoom, and navigation by gliding. Handheld maps allowed users to create layouts with multiple maps for comparison. A user study was performed to compare the effectiveness of Immersive ESS Visualizer to existing media, a 2D screen and paper maps. The user study investigated the effectiveness of Immersive ESS Visualizer for communication to a stakeholder. The most highly ranked features of Immersive ESS Visualizer included the file list, tab menus, handheld map, and zoom buttons. The study found that Zoom assisted participants with their comparison of data in VR, Immersive ESS Visualizer was good for inspecting hillshade, placing maps side-by-side was useful for comparing data, and participants adopted 3D positioning techniques to arrange maps to assist their analysis. Participant expertise was classified based on VR expertise, data expertise, map expertise, location expertise, and spatial technology expertise. Participants with more VR expertise found Immersive ESS Visualizer more effective. Participants had positive responses to their experiences communicating with the researcher while using VR, the zoom feature. The laser pointer and the facilitator’s 2D screen assisted participants to communicate while in the VR HMD. Immersive ESS Visualizer could potentially be extended to other datasets, the features available could be extended into a multi-user system.</strong></p>

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Section: Rendering Vector Data Onto Terrainmentioning

confidence: 99%

Immersive visualization for ecosystem services analysis and trade-offs

Powley

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Screen space point sampled shadows

Cited by 1 publication

References 23 publications

Immersive visualization for ecosystem services analysis and trade-offs

Immersive visualization for ecosystem services analysis and trade-offs

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