Draft:UIBVFED
Submission declined on 5 January 2024 by KylieTastic (talk).
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| Submission declined on 21 December 2023 by Theroadislong (talk). This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are: Declined by Theroadislong 5 months ago.
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| Submission declined on 18 December 2023 by Rich Smith (talk). This submission appears to be taken from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540961/. Wikipedia cannot accept material copied from elsewhere, unless it explicitly and verifiably has been released to the world under a suitably free and compatible copyright license or into the public domain and is written in an acceptable tone—this includes material that you own the copyright to. You should attribute the content of a draft to outside sources, using citations, but copying and pasting or closely paraphrasing sources is not acceptable. The entire draft should be written using your own words and structure. Declined by Rich Smith 5 months ago.
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Comment: Irrespective of the copyright status of the text, there do not appear to be any independent references that discuss the database, so the topic does not appear notable, per the general notability guideline. SmartSE (talk) 10:54, 19 December 2023 (UTC)
UIBVFED[1] is the first database made up of synthetic avatars that categorizes up to 32 facial expressions. The dataset is composed of 660 facial images (1080 x 1920) from 20 virtual characters each creating 32 facial expressions. The avatars represent 10 men and 10 women, aged between 20 and 80, from different ethnicities. Expressions are classified based on the six universal emotions (Anger, Disgust, Fear, Joy, Sadness, and Surprise) according to Faigin’s classification[2] whose reference is considered the standard to follow by animators and 3D artists. In addition to Faigin’s expression classification, the database provides the equivalence of the Facial Action Coding System (FACS)[3] with information about the position of the 51 facial landmarks in the 3D space to facilitate expression recognition. This is because the images of the facial expressions in the dataset were generated following the FAC guidelines. Therefore, the deformations that were applied to the 3D models have a direct correspondence with the Action Units (AUs) that are associated with each expression. This procedure ensures an objective labelling of all the images. Information about the landmarks for all characters and expressions is included in the dataset.
Figure 1 shows the 32 expressions plus the neutral one of one of the 20 characters in the UIBVFED database and their associated emotion.
The dataset is provided together with an interactive application, the UIBVFED application GUI, that allows the users to activate and control the expression intensity of the characters from different points of view.
References[edit]
- ^ Oliver, Miquel Mascaró; Alcover, Esperança Amengual (2020-04-06). "UIBVFED: Virtual facial expression dataset". PLOS ONE. 15 (4): e0231266. Bibcode:2020PLoSO..1531266O. doi:10.1371/journal.pone.0231266. ISSN 1932-6203. PMC 7135287. PMID 32251435.
- ^ Faigin, Gary (2012). The artist's complete guide to facial expression. Watson-Guptill.
- ^ "Facial Action Coding System (FACS) - A Visual Guidebook - iMotions". 2022-10-18. Retrieved 2023-12-18.
This article incorporates text by Miquel Mascaró-Oliver, Esperança Amengual-Alcover, Maria Francesca Roig-Maimó, Ramon Mas-Sansó available under the CC BY 4.0 license.- This article incorporates text by Miquel Mascaró Oliver, Esperança Amengual Alcover available under the CC BY 4.0 license.
- This article incorporates text by Miquel Mascaró-Oliver, Ramon Mas-Sansó, Esperança Amengual-Alcover, Maria Francesca Roig-Maimó available under the CC BY 4.0 license.
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