Bandara Dissanayake

Facial pore segmentation results can provide reliable evidence to simulate post-product pore conditions and provide product recommendations. However, accurately segmenting pores is challenging due to their small size, weak boundaries and dense distribution. It is also difficult to acquire precise annotation. Therefore, we formulate pore segmentation as a two-stage, weakly supervised task using both traditional and deep learning methods without human annotation. We propose a novel method called the pore segmentation network (PS-Net). Specifically, it contains pore feature extraction with coarse labels generated by a traditional method, as well as fine segmentation with progressively updated pseudo labels. Since pores provide high-frequency information about faces, we propose a high-frequency attention module that emphasizes low-level features. Moreover, we design a Bayesian module to identify pore shapes in high-level features. We establish a large-scale facial pore dataset with coarse labels that were generated via the difference of Gaussian (DoG) Pore method. PS-Net achieves the best performance on this dataset, proving its superiority compared with existing state-of-the-art segmentation methods.

Young women often complain about the daily fluctuation of their facial skin conditions. However, no objective study has been carried out on such changes. This study is aimed at quantitatively elucidating daily skin fluctuation and evaluating the efficacy of cosmetic skin care treatment. We developed the first portable and self-guided facial skin imaging device (eMR Pro) to reproducibly capture facial images at home. Two 8 week clinical studies were then conducted to analyze daily skin fluctuation of facial pore areas, roughness and redness in young Japanese women (n = 47 in study 1 and n = 57 in study 2) by collecting facial images three times a day, during the morning after wake-up, during the morning after face wash, and during the evening after face wash. After a 4 week baseline measurement period (week -4 to week -1), all subjects applied Galactomyces ferment filtrate (GFF, Pitera^®) skin care formula twice a day for 4 weeks (week 1 to week 4). These three skin conditions did exhibit different fluctuation patterns. The pore area and roughness showed the “morning after wake-up”-largest fluctuation pattern, whereas redness showed the “evening after face wash”-largest fluctuation pattern. GFF treatment significantly reduced the net values and delta fluctuation of pore area, roughness, and redness, which were consistently observed in two studies. In conclusion, the daily fluctuation of facial skin conditions is potentially a new target field for investigating healthy skin maintenance.

Background: Visible facial pores are an important cosmetic concern especially among young females. Number of different methodologies is used today to assess facial pores and efficacy of technologies. Main limitations of these methods are, however, (a) moderate correlation with visual perception, (b) characterization is mostly limited to size or number of pores, (c) measurement is limited to a smaller area of face, and (d) operational difficulties. In order to address these limitations, we developed a 2D image analysis tool to assess and characterize visible facial pores.Materials and Methods: Two clinical studies were conducted with northeast Asian skin type females. In the first study, 40 subjects age between 20 and 40 with different degree of pore severity were recruited. In the second study, 15 subjects age between 20 and 40 with enlarged pores were recruited to evaluate pore product efficacy. In both studies, full face images were taken using Visia‐CR and assessed by means of the newly developed tool and visual grading.Results: A high correlation between visual grading and pore size was obtained (r = 0.86). New methodology was able to differentiate products similar to visual grading.Conclusion: Novel pore image analysis method using 2D skin surface imaging with standard photography has been developed and validated. In addition to pore size measurements, we propose this method to be used to measure pore shape, color, and orientation for a comprehensive characterization of facial pores.

The characteristics of powder coatings manufactured through a novel processing technique based on nonisothermal Nlow‐induced phase inversion granulation enhanced by fluid injection to promote phase inversion and particle formation from melt state is summarized. Experiments were carried out in a purpose‐built granulator, which operates in a parallel disk rotor‐stator arrangement, so that the mechanism of granulation could be studied. The product of this intensive granulation was compared with that of the conventional powder coating manufacturing process. Understanding the mechanism of intensive granulation helped to redesign the equipment that resulted in smaller particles. Pigment dispersion characteristics were improved by intensive granulation. Also, the particle size span can be significantly reduced by dry granulation and gas‐phase granulation, and the flowability can be improved by wet granulation. Chemical analysis of particles by Fourier transform infrared spectroscopic analysis showed that the injection of coolant fluid had no effect on the chemical composition. © 2011 American Institute of Chemical Engineers AIChE J, 2012