SwePub - sökning: WFRF:(Aaro Gustav 1995 )

Numrering	Referens	Omslagsbild	Hitta
1.	Aaro, Gustav, 1995-, et al. (författare) Toolset for Run-time Dataset Collection of Deep-scene Information 2020 Ingår i: Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS). - Cham : Springer. - 9783030681098 ; , s. 224-236 Konferensbidrag (refereegranskat)abstract Virtual reality (VR) provides many exciting new application opportunities, but also present new challenges. In contrast to 360° videos that only allow a user to select its viewing direction, in fully immersive VR, users can also move around and interact with objects in the virtual world. To most effectively deliver such services it is therefore important to understand how users move around in relation to such objects. In this paper, we present a methodology and software tool for generating run-time datasets capturing a user’s interactions with such 3D environments, evaluate and compare different object identification methods that we implement within the tool, and use datasets collected with the tool to demonstrate example uses. The tool was developed in Unity, easily integrates with existing Unity applications through the use of periodic calls that extracts information about the environment using different ray-casting methods. The software tool and example datasets are made available with this paper.

Aaro, Gustav, 1995-, et al. (författare)
Toolset for Run-time Dataset Collection of Deep-scene Information
2020
Ingår i: Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS). - Cham : Springer. - 9783030681098 ; , s. 224-236
Konferensbidrag (refereegranskat)abstract
- Virtual reality (VR) provides many exciting new application opportunities, but also present new challenges. In contrast to 360° videos that only allow a user to select its viewing direction, in fully immersive VR, users can also move around and interact with objects in the virtual world. To most effectively deliver such services it is therefore important to understand how users move around in relation to such objects. In this paper, we present a methodology and software tool for generating run-time datasets capturing a user’s interactions with such 3D environments, evaluate and compare different object identification methods that we implement within the tool, and use datasets collected with the tool to demonstrate example uses. The tool was developed in Unity, easily integrates with existing Unity applications through the use of periodic calls that extracts information about the environment using different ray-casting methods. The software tool and example datasets are made available with this paper.

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