In response to consumer demand for personalized content, the customized cosmetics market continues to grow, centering on the beauty industry. This study was conducted to find out the awareness and brand awareness of customized cosmetics. From February 2023, a total of 313 adult men and women residing in Korea were surveyed on the degree of awareness of customized cosmetics, domestic and foreign brand awareness and use experience, evaluation of major brands of customized cosmetics, and expectations. Statistical analysis was performed on the data collected after the survey using SPSS version 25.0 for Windows. As a result, the recognition level of customized cosmetics was 'normal' (45.4%), and the product path was 'online advertisement' (42.8%), 'new purchase and plan to use' of customized cosmetics (62.6%), and product purchase and use plan. As for the place, 'online shopping mall' (46.3%) accounted for a high proportion. Brand recognition and usage status at home and abroad was 'know' (53.6%), the number of recognized brands was 'more than 4' (53.0), and the evaluation of domestic and foreign brand image was very high as 'positive' (80.7%). In terms of product diversity, 'satisfaction' (68.6%) was found to be high. The experience of purchasing and using domestic and foreign brands for customized cosmetics was higher than that of foreign brands, showing a significant difference. As for the purchase of customized cosmetics and the level of expectation for domestic and foreign brands, the expectation level was high with 'expectation' for domestic brands (92.9%) and 'expectation' for foreign brands (94.8%). As a result of comparative analysis by classifying groups according to general characteristics, the degree of recognition of customized cosmetics and intention to purchase showed significant differences in part according to gender, residential area, and final education level. Domestic and foreign brand awareness and experience of customized cosmetics, and expectations for customized cosmetics showed differences according to gender, region of residence, and final education level. Therefore, based on these results, it can be applied as basic data for research on the activation of customized cosmetics.
In this paper, we are proposing improved vanishing points detection and segments labeling methods for inside wall frame detection from indoor image of a piece of having a colour RGB. A lot of research related to recognizing the frame of artificial structures from the image is being performed due to increase in demand for AR technology. But detect the inside wall frame in indoor images have many objects that caused the occlusion is still a difficult issue. Inner wall frame detection methods are usually segment labeling methods and detect vanishing point methods are used together. In order to improve the vanishing point detection method we proposed using inner wall orthogonality which forms the cube. Also we proposed labeling method using tree based learning and superpixel based segmentation method for labelingthe segments in indoor images. Finally, in experiments have shown improved results about inside wall frame detection according to our methods. Hoiem은 표면정보를 이용하여 벽면을 분류하는 방법 을 제안하였다 [2]. Hedau는 Hoiem의 방법을 개선하기 위 하여 실내 구조가 3차원 Box형태를 띄고 있다는 가정하 ISSN 1598-0170 (Print)
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