| Autor: |
Amany Al Luhaybi, Fahad Alqurashi, Georgios Tsaramirsis, Seyed M. Buhari |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 9, Iss 8, p 1697 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app9081697 |
| Popis: |
Although olfaction can enhance the user’s experience in virtual environments, the approach is not widely utilized by virtual contents. This is because the olfaction displays are either not aware of the content in the virtual world or they are application specific. Enabling wide context awareness is possible through the use of image recognition via machine learning. Screenshots from the virtual worlds can be analyzed for the presence of virtual scent emitters, allowing the olfactory display to respond by generating the corresponding smells. The Convolutional Neural Network (CNN), using Inception Model for image recognition was used for training the system. To evaluate the performance of the accuracy of the model, we trained it on a computer game called Minecraft. The results and performance of the model was 97% accurate, while in some cases the accuracy reached 99%. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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