MD SHAFIUZZAMAN

BSSE 0322

Supervised by:Dr. Mohammad Shoyaib&Emon Kumar Dey

Problem Definition

Proposed Method

Experimental Result

Future Plan

Contents

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Garments Texture Classificationby Analyzing

Local Texture Descriptors

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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

ForecastFashionTrend

ManualAnnotations

Infeasible

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Any Solution…

No Complete Solution so far…

Some Partial Approaches..

Texture MatchColor Not Match

Match Not Match

Clothes Matching for Blind and ColorBlind 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

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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

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Category-I Category-II Category-III

Objective of This Thesis

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Contribution of this thesis:

Propose a Pioneer method for Garment Texture Classification

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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

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PROPOSED METHOD

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Garment Texture Classification Method

Uniform Color Stripe Print

Input Image

Masked

Image

Background

Removed

Segmented

Image

Region of Interest

Pre-Processing Steps

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Identify Uniform Color using

Color Descriptor

Uniform Color

Yes

No

Input Image

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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

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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

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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

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Result (Girls’ Dress)

Category Precision Recall

Uniform Color 0.89 0.98

Print 0.93 0.77

Stripe 0.72 0.60

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Result (Men Shirt)

Category Precision Recall

Uniform Color 0.94 0.85

Print 0.86 0.90

Stripe 0.86 0.93

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Future Plan

• Compare in more descriptor-classifier combinations

• Fit the method more categories

• Enhance for other garment accessories like shoes, bags

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Any Question?

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