Improving the Accuracy of Beauty Product Recommendations by Assessing Face Illumination Quality

We focus on addressing the challenges in responsible beauty product recommendation, particularly when it involves comparing the product's color with a person's skin tone, such as for foundation and concealer products. To make accurate recommendations, it is crucial to infer both the product attributes and the product specific facial features such as skin conditions or tone. However, while many product photos are taken under good light conditions, face photos are taken from a wide range of conditions. The features extracted using the photos from ill-illuminated environment can be highly misleading or even be incompatible to be compared with the product attributes. Hence bad illumination condition can severely degrade quality of the recommendation. We introduce a machine learning framework for illumination assessment which classifies images into having either good or bad illumination condition. We then build an automatic user guidance tool which informs a user holding their camera if their illumination condition is good or bad. This way, the user is provided with rapid feedback and can interactively control how the photo is taken for their recommendation. Only a few studies are dedicated to this problem, mostly due to the lack of dataset that is large, labeled, and diverse both in terms of skin tones and light patterns. Lack of such dataset leads to neglecting skin tone diversity. Therefore, We begin by constructing a diverse synthetic dataset that simulates various skin tones and light patterns in addition to an existing facial image dataset. Next, we train a Convolutional Neural Network (CNN) for illumination assessment that outperforms the existing solutions using the synthetic dataset. Finally, we analyze how the our work improves the shade recommendation for various foundation products.Comment: 7 pages, 5 figures. Presented in FAccTRec202

Control / contrôle: comparing discourses of power and rebellion in hair care products

Thesis (M.A.) University of Alaska Fairbanks, 2017Since the Antiquity, female hair has been a powerful social semiotic, used to determine women's sexuality, mental states, and adherence to gender norms. As a result of this extensive signifying power, many disciplinary practices have evolved to regulate female hair. In this thesis, I use critical discourse analysis methods to determine what ideologies are present on consumer hair care products. I investigate a selection of products found within a Fairbanks, AK beauty store, analyzing the English and French text on the labels. The results of this analysis show that hair product labels directly address the disciplinary practices that circulate through our culture, often referencing control, aggression, and defensive relationships. The language to evoke control is modified slightly between Anglo-American and French and Franco-Canadian contexts, with the former more likely to use managerial terms in the discourse. Hair product labels also appropriate language of resistance, ultimately creating an adversarial relationship between the consumer and nature

Root, Tuber and Banana Food System Innovations

This open access book describes recent innovations in food systems based on root, tuber and banana crops in developing countries. These innovations respond to many of the challenges facing these vital crops, linked to their vegetative seed and bulky and perishable produce. The innovations create value, food, jobs and new sources of income while improving the wellbeing and quality of life of their users. Women are often key players in the production, processing and marketing of roots, tubers and bananas, so successful innovation needs to consider gender. These crops and their value chains have long been neglected by research and development, hence this book contributes to filling in the gap. The book features many outcomes of the CGIAR Research Program in Roots, Tubers and Banana (RTB), which operated from 2012-21, encompassing many tropical countries, academic and industry partners, multiple crops, and major initiatives. It describes the successful innovation model developed by RTB that brings together diverse partners and organizations, to create value for the end users and to generate positive economic and social outcomes. RTB has accelerated the scaling of innovations to reach many end users cost effectively. Though most of the book’s examples and insights are from Africa, they can be applied worldwide. The book will be useful for decision makers designing policies to scale up agricultural solutions, for researchers and extension specialists seeking practical ideas, and for scholars of innovation

Avoiding Ad Avoidance: Factors Affecting The Perception Of Online Banner Ads

This dissertation examined the effect of search type, ad saliency, and ad repetition on the perception of online banner advertisements. In the first study, 48 student participants conducted simulated search tasks using mixed factorial design where search type (known-item vs. exploratory) was manipulated within-subject and the banner saliency level (low (black and white) vs. medium (color) vs. high (color animation)) was manipulated between subjects. The results showed a significant effect for search type, such that during an exploratory search task the participants had a higher average number of eye fixations on the banner ads compared with known-item search. In addition, there was a significant difference between high and low ad saliency levels, such that participants exposed to low salient ads had a higher average number of eye fixations on the banner ads as compared with high salient ads. There was no significant effect of ad repetition on ad perception. A second study replicated the original experimental design but used four novice Internet users. The results from the second study provide preliminary support to the asymptotic habituation model, which predicts an inverse decline of an orienting response to banner ads as a function of repetition. This dissertation concludes with applicable design recommendation for banner ad deployment to ensure visibility while maintaining a positive user experience.Doctor of Philosoph

Root, Tuber and Banana Food System Innovations

This open access book describes recent innovations in food systems based on root, tuber and banana crops in developing countries. These innovations respond to many of the challenges facing these vital crops, linked to their vegetative seed and bulky and perishable produce. The innovations create value, food, jobs and new sources of income while improving the wellbeing and quality of life of their users. Women are often key players in the production, processing and marketing of roots, tubers and bananas, so successful innovation needs to consider gender. These crops and their value chains have long been neglected by research and development, hence this book contributes to filling in the gap. The book features many outcomes of the CGIAR Research Program in Roots, Tubers and Banana (RTB), which operated from 2012-21, encompassing many tropical countries, academic and industry partners, multiple crops, and major initiatives. It describes the successful innovation model developed by RTB that brings together diverse partners and organizations, to create value for the end users and to generate positive economic and social outcomes. RTB has accelerated the scaling of innovations to reach many end users cost effectively. Though most of the book’s examples and insights are from Africa, they can be applied worldwide. The book will be useful for decision makers designing policies to scale up agricultural solutions, for researchers and extension specialists seeking practical ideas, and for scholars of innovation