Figaro-tresses: a dataset for evaluating hair assembly features before and after cosmetic treatment

Tools

Sarvardi, Mattia and Daniels, Gabriela and Tamburic, Slobodanka and Muhammad, Umar Riaz and Benini, Sergio (2020) Figaro-tresses: a dataset for evaluating hair assembly features before and after cosmetic treatment. Data in Brief. ISSN 2352-3409

Type of Research:	Article
Creators:	Sarvardi, Mattia and Daniels, Gabriela and Tamburic, Slobodanka and Muhammad, Umar Riaz and Benini, Sergio
Description:	A published database is composed of 1,080 images taken from 120 hair tresses made of medium blond, fine Caucasian hair with the aim to facilitate quantitative and qualitative studies about shampoo and conditioner efficacies. This data has value for: Providing further insight into how to develop quantitative and qualitative studies about shampoo and conditioner efficacies; Developing models and classification strategies to predict the objective hair assembly features after a cosmetic treatment; Deepening the knowledge on how different hair interacts differently with the compounds in the products; By evaluating the prediction of automatic models, suggestions can be provided to consumers and fashion practitioners.
Official Website:	https://www.journals.elsevier.com/data-in-brief
Keywords/subjects not otherwise listed:	hair, cosmetics, shampoo, conditioner, hair assembly, hair tresses, hair fibre
Publisher/Broadcaster/Company:	Science Direct, Elsevier
Your affiliations with UAL:	Colleges > London College of Fashion
Date:	3 July 2020
Digital Object Identifier:	10.1016/j.dib.2020.105964
Date Deposited:	08 Jul 2020 14:02
Last Modified:	10 Jul 2020 05:18
Item ID:	15836
URI:	https://ualresearchonline.arts.ac.uk/id/eprint/15836

Repository Staff Only: item control page | University Staff: Request a correction