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人工智慧在流行趨勢研究的應用
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- 並列題名:AI application in Fashion Trend
- 作者: 顏志晃(Chih-Huang Yen, Ph. D.)著
- 出版社:元華文創
- 出版年:2020
- EISBN:9789577111883 EPUB
- 格式:EPUB 流式
- 附註:內容為英文
Consumer behavior is complicated. In the cosmetic market, personal intuition and fashion trends for colour selection are guidelines for consumers. A systematic method for female facial skin-color classification and an application in the makeup market are proposed in this study. In this paper, face recognition with a large number of images is first discussed. Then, an innovative method for colour capturing at selected points is presented and complexion-aggregated analysis is performed. This innovative method is an extension of face-recognition theory. Images in RGB format are converted to Lab-space format during data collection and then Fuzzy C-means theory is utilized to cluster and group the data. The results are classified and grouped in Lab value and RGB index. Two programs are created. The first program, “FaceRGB”, captures colour automatically from images. The second program, “ColorFCM”, clusters and groups the skin-color information. The results can be used to assist an expert system in the selection of customized colours during makeup and new-product development. In the study case, with more than 10,000 Asian women photos, FaceRGB for automatic skin color capture, obtained skin color data and then divided by ColorFCM eighteen group results. In the end, the study combined with Merck's colour trend forecast, connected the clustering skin colour with six Merck's idea skin colour to do the pair, the results will be applied to cosmetic, and more clearly realize the value of research and the future development of the application.
- 封面
- 版權
- ABOUT THE AUTHOR作者簡介
- PREFACE作者序
- SUMMARY
- ACKNOWLEDGEMENTS
- LIST OF SYMBOLS AND ABBREVIATIONS
- CHAPTER 1 INTRODUCTION
- 1.1 Related research
- 1.2 Market Assessment from Merck
- 1.3 Outline of this study
- CHAPTER 2 LITERATURE REVIEW
- 2.1 The choice for colour space
- 2.2 Taguchi Methods
- 2.3 Fuzzy C-means
- 2.4 Facial recognition system
- CHAPTER 3 IMPLEMENTATION METHOD
- 3.1 6 points colour detection
- 3.2 Verification for 6 points to detect facial colour
- CHAPTER 4 CASE STUDY
- 4.1 FaceRGB
- 4.2 ColorFCM
- CHAPTER 5 RESULTS & DISCUSSION
- 5.1 Experimental verification
- 5.2 RGB & YCC conversions
- 5.3 Training samples for FaceRGB
- 5.4 RGB with a large quantity of images
- 5.5 ColorFCM result by Fuzzy C-means
- CHAPTER 6 APPLICATION
- 6.1 Connection between the colour clusters and Merck makeup trends
- 6.2 For personal application
- 6.3 For trend applications
- 6.4 Conclusion
- REFERENCES
今日租書可閱讀至2024-10-19