A Robust Dominant Colour Extraction and Real-Time Trend Prediction Based on Transformer Network

A Robust Dominant Colour Extraction and Real-Time Trend Prediction Based on Transformer Network | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 9 January 2025 V1 Latest version Share on A Robust Dominant Colour Extraction and Real-Time Trend Prediction Based on Transformer Network Authors : Kishore Kumar R 0000-0002-5010-6781 [email protected] and Kaustav Sengupta Authors Info & Affiliations https://doi.org/10.22541/au.173639057.76036276/v1 201 views 111 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This paper focuses on predicting colour trends in fashion, a constantly evolving form of human expression. Current literature lacks methods to effectively detect and analyze colours in fashion apparel images for accurate trend forecasting. To address this gap, the study collects apparel images from different regions of India to extract and analyze the dominant colours specific to India. The proposed approach uses YOLO object detection to identify human key points within the images, followed by isolating the top and bottom wear. These areas are analyzed using the Colour Thief algorithm to extract dominant colours, which are then converted into hex codes and mapped to corresponding colour names. These colours are further grouped into broader categories and analyze as time series. Using Patch transformers (PatchTST), the model predicts future colour trends for the upcoming seasons. This system aims to assist Indian retailers by providing insights into emerging colour patterns, enabling them to better plan and strategize their merchandise offerings. Supplementary Material File (colour_real_time.pdf) Download 5.12 MB Information & Authors Information Version history V1 Version 1 09 January 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence colour analysis time series prediction transformer Authors Affiliations Kishore Kumar R 0000-0002-5010-6781 [email protected] National Institute of Fashion Technology - Chennai Campus View all articles by this author Kaustav Sengupta National Institute of Fashion Technology - Chennai Campus View all articles by this author Metrics & Citations Metrics Article Usage 201 views 111 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Kishore Kumar R, Kaustav Sengupta. A Robust Dominant Colour Extraction and Real-Time Trend Prediction Based on Transformer Network. Authorea . 09 January 2025. DOI: https://doi.org/10.22541/au.173639057.76036276/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. 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