| Title |
A standardized set of 3-D objects for virtual reality research and applications
|
|---|---|
| Published in |
Behavior Research Methods, June 2017
|
| DOI | 10.3758/s13428-017-0925-3 |
| Pubmed ID | |
| Authors |
David Peeters |
| Abstract |
The use of immersive virtual reality as a research tool is rapidly increasing in numerous scientific disciplines. By combining ecological validity with strict experimental control, immersive virtual reality provides the potential to develop and test scientific theories in rich environments that closely resemble everyday settings. This article introduces the first standardized database of colored three-dimensional (3-D) objects that can be used in virtual reality and augmented reality research and applications. The 147 objects have been normed for name agreement, image agreement, familiarity, visual complexity, and corresponding lexical characteristics of the modal object names. The availability of standardized 3-D objects for virtual reality research is important, because reaching valid theoretical conclusions hinges critically on the use of well-controlled experimental stimuli. Sharing standardized 3-D objects across different virtual reality labs will allow for science to move forward more quickly. |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 10 | 37% |
| United Kingdom | 6 | 22% |
| Germany | 2 | 7% |
| Austria | 1 | 4% |
| Ireland | 1 | 4% |
| Unknown | 7 | 26% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 56% |
| Scientists | 11 | 41% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 75 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 32% |
| Student > Master | 16 | 21% |
| Researcher | 8 | 11% |
| Student > Doctoral Student | 5 | 7% |
| Student > Bachelor | 3 | 4% |
| Other | 7 | 9% |
| Unknown | 12 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 19 | 25% |
| Neuroscience | 11 | 15% |
| Computer Science | 7 | 9% |
| Engineering | 5 | 7% |
| Medicine and Dentistry | 4 | 5% |
| Other | 12 | 16% |
| Unknown | 17 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 25. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 September 2020.
All research outputs
#1,524,799
of 25,382,440 outputs
Outputs from Behavior Research Methods
#138
of 2,526 outputs
Outputs of similar age
#29,858
of 329,377 outputs
Outputs of similar age from Behavior Research Methods
#5
of 39 outputs
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We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.