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Garment Texture Classification for Automated Product Suggestion

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This document presents a proposed method for classifying garment textures by analyzing local texture descriptors. It begins with background on the growing e-commerce market for garments and accessories. It then discusses issues with existing approaches and the need for an automated solution. The proposed method involves preprocessing images, identifying uniform colors, computing texture descriptors, and classifying patterns using random forest. It provides experimental results testing various descriptors on dresses and shirts, achieving over 90% accuracy with completed LBP. Future plans include expanding the method to more categories and accessories.

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MD SHAFIUZZAMAN BSSE 0322 Supervised by: Dr. Mohammad Shoyaib & Emon Kumar Dey
Problem Definition Proposed Method Experimental Result Future Plan Contents 3/9/2015 2
Garments Texture Classification by Analyzing Local Texture Descriptors 3/9/2015 3
US Garment Accessories e-shopping Revenue in 2013: 44.7 Billion Dollars [1] 45% of Consumers Prefer Shopping for Clothes Online [2] 64% Consult A Fashion Retailer's Website Before Making a purchase [2] [1] http://www.statista.com/statistics/278890/us-apparel-and-accessories-retail-e-commerce-revenue [2] https://econsultancy.com/blog/7960-45-of-consumers-prefer-shopping-for-clothes-online3/9/2015 4
Identify User Demand Forecast Fashion Trend Manual Annotations Infeasible 3/9/2015 5
Any Solution… No Complete Solution so far… Some Partial Approaches..
Texture Match Color Not Match Match Not Match Clothes Matching for Blind and Color Blind People [3] (2010) [3] Y. Tian, S. Yuan, “Clothes Matching for Blind and Color Blind People”, Springer, Computers Helping People with Special Needs, Lecture Notes in Computer Science, Volume 6180, 2010, pp 324-331 3/9/2015 7
Dress Short Pants Identify Category of Garment Accessories [4] (2014) [4] M. Manfredi. C. Grana, S. Calderara, R. Cucchiara, “A complete system for garment segmentation and color classification”, Springer Machine Vision and Applications May 2014, Volume 25, Issue 4, pp 955-969 3/9/2015 8
Category-I Category-II Category-III Objective of This Thesis 3/9/2015 9
Contribution of this thesis: Propose a Pioneer method for Garment Texture Classification 3/9/2015 10
Issues related to Garment Textures: Full of shadows and wrinkles Large intra-class variations in appearance, orientation & scale Designed with complex patterns and varieties of colors 3/9/2015 11
PROPOSED METHOD 3/9/2015 12
Garment Texture Classification Method Uniform Color Stripe Print
Input Image Masked Image Background Removed Segmented Image Region of Interest Pre-Processing Steps 3/9/2015 14
Identify Uniform Color using Color Descriptor Uniform Color Yes No Input Image 3/9/2015 15
Compute Texture Pattern Using Texture Descriptors • LBP of Sign Component (Basic LBP) • LBP of Magnitude Component • LBP of Center Pixel3/9/2015 16
Classify Using Random Forest Classifier Tree1 Tree2 Treen Vote1 Vote2 Vote3 Voting 3/9/2015 17
Dataset • Publicly available at the website: http://imagelab.ing.unimore.it/fashion_dataset.asp • Men Shirts and Girls’ Dresses were separated • Then images were manually categorized into three classes including uniform color, stripe and print Girls’ Dress Men Shirt Uniform Color 2441 200 Stripe 173 200 Print 1142 200 3/9/2015 18
Accuracy of The Descriptors Texture Descriptor Accuracy LBP 84.82 Mean LBP 79.22 Humming LBP 82.03 LTP 76.06 Fuzzy LBP 87.43 Noise Resistance LBP 92.10 Completed LBP 93.87 3/9/2015 19
Result (Girls’ Dress) Category Precision Recall Uniform Color 0.89 0.98 Print 0.93 0.77 Stripe 0.72 0.60 3/9/2015 20
Result (Men Shirt) Category Precision Recall Uniform Color 0.94 0.85 Print 0.86 0.90 Stripe 0.86 0.93 3/9/2015 21
Future Plan • Compare in more descriptor-classifier combinations • Fit the method more categories • Enhance for other garment accessories like shoes, bags 3/9/2015 22
Any Question? 3/9/2015 23

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Garment Texture Classification for Automated Product Suggestion