Recommender System - Adapted-Fashion

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Personalized cooperative design. Page 6. 6. Photo. Modaris. Optitex. Clo3D. Personalized virtual fitting process. Personalized cooperative design. Page 7. 7.
Building an Intelligent Garment Shopping Platform for Personalized Cooperative Design By Xianyi Zeng, Pascal Bruniaux and Xiao Chen ENSAIT Textile Institute, Roubaix, France

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Building an intelligent garment e-shop

Current garment e-shopping (>40% of benefits in Europe): 1) E-catalogs based on classification 2) Visualization: photos (mostly) and 3D virtual objects 3) Virtual perception: visual effects only, static fitting

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Building an intelligent garment e-shop

E-shopping in the future: - More complete virtual environment => 1) Personalized fitting 2) Virtual perception: visual effects (static and dynamic) + fabric hand + comfort + controlled virtual ambiance 3) Virtual sales advisor => professional product/consumer knowledge + Searching engine: personalized product recommender system

- A cooperative garment design platform => 1) Interactions between consumer, designer and material developer 2) Searching engine: from consumer’s needs to new technical parameters (styles, patterns, fabrics, colors, textures, …): personalized design recommender system

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Personalized cooperative design Extension to a new production model (small series, fast fashion) Task allocation, scheduling

Transporter 1

LCA

Mini factory 1

LOGISTIC PLATEFORM

Stock 1

Body shape classification

International supply chain

production orders

Technical Constraints cost

CO-DESIGN PLATEFORM

Ease allowance comfort Real & virtual shop

Recommendatio n

Product tracking

Perception& emotion modeling Virtual fitting process 4

Personalized cooperative design Personalized virtual fitting process 1

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5

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Co-design : new concept for garment design and production, man/garment interface

Garment CAD software: inputs => fabric mechanical and optical properties garment patterns outputs => static and dynamic virtual garments 5

Personalized cooperative design Personalized virtual fitting process Photo

Modaris

Optitex

Clo3D

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Personalized cooperative design Classification of parametric 3D body shapes Lost of information with classical classification procedures

Phase 2

Phase 1

Normalization

3D Object

Preprocessing

Parameterization

Extracting shape’s 3D shape description signature

Phase 3

Classification

Identifying N body shapes

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Personalized cooperative design Ease allowance generation: fitting comfort

Principles 1) Selecting relevant body measurements 2) Formalization of fitting comfort 3) Determination of comfort oriented garment patterns Relevant body measurements

Human sensory evaluation

Fuzzy Logic Controller

standard ease + dynamic ease

Garment pattern generation

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Personalized cooperative design Ease allowance generation: fitting comfort

Data acquisition: 1) Taking body measurements 2) Evaluating comfort levels at different postures

Adjustable trousers

Relevant body measurements related to the gluteal region and the trouser of normal size 9

Personalized cooperative design Ease allowance generation: fitting comfort

Comparison between fuzzy pattern (blue line) and classical pattern (red line) 10

Personalized cooperative design Co-design: control of perception by adjusting technical parameters

Inputs:

Outputs:

Stretch-weft Stretch-warp Shear Bending-weft Bending-warp Buckling ratio Bulking-stiffness

Fiber perception: naturel or synthetic

Ʃ

Process perception: weaving or knitting Flexible - Rigid Rough – Smooth Soft (surface) - Hard Draping perception Thick - Thin

Basic mass

Heavy - Light

Thickness

Brillant - Matt Hot color – Cold color

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Personalized cooperative design Co-design: control of perception by adjusting technical parameters Initial prototype

Bending 10=>30

Shearing 5=>30

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Personalized cooperative design Evaluating fabric hand from virtual prototypes Modelling visual/tactile interactions - Interpret tactile information from virtual prototype - Adjust model parameters according to the desired tactile property in order to design the most appropriate material

Upper part Pliable

Very

Loose

Quite

Fuzzy

Fairly

Thin

Quite

Stretchy

Fairly

Lower part Tactile information

Pliable

Fairly

Tight

Fairly

Slippery

Very

Thin

Quite

Draped

Quite 13

Personalized cooperative design Recommender System: evaluating a new style relative to a specific body shape and an expected fashion theme

Output of Model I Relevancy (BR, T)

Output of Model II Relevancy (BR_de, T)

whether a garment design is feasible for a specific body shape in terms of promotion of its relevancy to the fashion theme ? 14

Personalized cooperative design Recommender System: 

Target Market Three different body shapes of personalized consumers



Design Objective promotion of the fashion themes: “Attractive” for male overcoats



New Garment Design Styles

de1: Totally belong to Chester de2: Totally belong to Duffle de3: Fairly belong to Chester AND a little belong to Ulster Styles

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Personalized cooperative design Recommender System:

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Personalized cooperative design

Conclusion: Summary of our projects: - Consumer perception and emotion-oriented design - Integration of professional fashion knowledge - Integration of virtual reality and real sample’s data Consideration on fashion design of people with physical Limitations: - Identification of physical limitations from video – animation software - Characterization of consumer perception and emotion - Personalized virtual garment design process - Virtual fitting of consumers with integration of perceptions and emotions and physical limitations 17