Title: In Situ Questionnaires for Haptic Experience in VR
Language: English
Authors: Varečková, Jana 
Qualification level: Diploma
Keywords: haptics; VR; questionnaire; real objects; virtual models
Advisor: Kaufmann, Hannes  
Assisting Advisor: Vonach, Emanuel 
Issue Date: 2020
Number of Pages: 85
Qualification level: Diploma
Abstract: 
Real (physical) objects are being used in virtual reality (VR), where users see its 3D model and interact with the real object. However, creating or finding an exact replica from a 3D model can be costly. As users can adapt to small proprioceptive mismatches, the objects used do not have to be identical. There is no questionnaire established in virtual reality, which would focus on object features and would be able to compare objects and their suitability to be used as substitutes.Therefore, our aim was to design a questionnaire, which would distinguish, whether the real object corresponds to a 3D model the user sees in VR based on the evaluation of object properties. To avoid incorrect completion of the questionnaire due to faulty memory, this questionnaire is asked while the users are still in VR and can interact with the object. Therefore, we named it the In-Situ-Questionnaire. To research different aspects of developing a suitable questionnaire, we designed three slightly different questionnaires, where the main change is a scale. To verify validity of the In-Situ-Questionnaires, a simple VR environment was created to test it during user studies. There the users could seetheir hands and interact with three different chairs. Each chair was evaluated separately.For comparison with the In-Situ-Questionnaires, we also created a Post-Questionnaire,where we used commonly used questionnaires.Analyzing of the responses from the user studies, we concluded that the designed In-Situ-Questionnaires are able to compare different objects and indicate, which object is themost suitable as a substitute.
URI: https://doi.org/10.34726/hss.2020.67603
http://hdl.handle.net/20.500.12708/16172
DOI: 10.34726/hss.2020.67603
Library ID: AC16071858
Organisation: E193 - Institut für Visual Computing and Human-Centered Technology 
Publication Type: Thesis
Hochschulschrift
Appears in Collections:Thesis

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