Fashion – Dataconomy https://dataconomy.ru Bridging the gap between technology and business Tue, 27 Feb 2024 14:46:33 +0000 en-US hourly 1 https://dataconomy.ru/wp-content/uploads/2022/12/cropped-DC-logo-emblem_multicolor-32x32.png Fashion – Dataconomy https://dataconomy.ru 32 32 Shop smarter with AR try-on technologies https://dataconomy.ru/2024/02/27/ar-try-on-technologies/ Tue, 27 Feb 2024 14:45:28 +0000 https://dataconomy.ru/?p=49191 Think about the last time you bought clothes online. Did the jeans hug your curves just right? Was that sweater’s color as vibrant in person? Online shopping can be a gamble, but AR try-on technologies are here to change that. Forget about guessing fits and imagining colors, this technology lets you see those items on […]]]>

Think about the last time you bought clothes online. Did the jeans hug your curves just right? Was that sweater’s color as vibrant in person? Online shopping can be a gamble, but AR try-on technologies are here to change that.

Forget about guessing fits and imagining colors, this technology lets you see those items on yourself before clicking “buy”!

Let’s delve into how this technology works, its benefits, and how it’s set to shape the future of fashion retail.

AR try-ons are reshaping online shopping

AR try-on technologies essentially allow shoppers to “try on” clothes and accessories virtually. Utilizing your smartphone or computer’s camera, AR technology superimposes realistic images of garments and accessories onto your body.

This enables you to gauge how an item might look, fit, and move on you, all without physically donning it.

A bit of tech magic

So, how do AR try-on technologies for fashion work? Well:

  1. Product digitization: The first step involves creating highly accurate 3D models of clothing items or accessories. This process may involve 3D scanning or utilization of existing design and pattern data
  2. Body tracking and size matching: Sophisticated AI algorithms analyze your body shape, measurements, and movements in real-time through your camera’s feed. This data is used to ensure the virtual garment is appropriately scaled and draped over your body
  3. Augmented reality overlay: Finally, the 3D model of the selected item is superimposed onto your live image, creating the illusion that you’re physically wearing it. You can often rotate, zoom in, and examine the clothing from different angles

Advanced AR try-on solutions go beyond simply overlaying the garment. They consider fabric properties like texture, drape, and how the item responds to movement. This means you’ll get a sense of how the material flows, whether it feels restrictive or loose, and if it shimmers or wrinkles under different lighting.

Within just a single year, the evolution of machine learning applications has been nothing short of breathtaking. Where once the focus was primarily on generating text, we now see a stunning explosion of capabilities. AI-powered systems can conjure realistic images, craft captivating videos, and revolutionize shopping experiences with virtual try-ons. The pace of transformation is remarkable, suggesting a future where the ways we create, interact, and consume content will be forever changed.

And all these are possible today thanks to complex machine learning algorithms the whole tech world has been working on for a long time. AI and machine learning’s impact on startups can be seen more clearly with each passing day.

Brands are already adopting it

Many fashion brands and retailers like Gucci, Burberry, and Chanel, are already embracing AR try-on technology.

Using Snapchat’s popular AR Lens feature, the Gucci brand was the first to break new ground in this area, offering Snapchat users the opportunity to try on shoes before they even buy them, let alone go to the store.

This innovative approach showed brands and us a whole new potential: We don’t have to leave our homes to try fashion products. Since then, many brands have worked on this and strived to develop AR-try on technology. One such brand is ZERO10.

ZERO10, a prominent player in the fashion industry’s virtual try-on (VTO) space, has introduced its novel Multi-Task ML model. This development, mirroring concepts used by industry giants like Tesla, has the potential to transform AI-powered solutions specifically within real-time AR try-on experiences.

A fundamental challenge of VTO lies in achieving real-time processing without sacrificing visual quality. AR try-on for apparel and accessories requires complex machine learning (ML) tasks like 3D body tracking and multi-class segmentation, each demanding real-time execution.

With traditional sequential ML model processing, performance limitations have been a consistent problem. ZERO10’s Multi-Task ML model offers a solution as explained on Zero10’s tech page.

ZERO10 AR try-on
Balancing real-time processing and quality is a key challenge in virtual try-on and ZERO10 is spot on (Image credit)

Finding the perfect clothes is amazing, but what about the makeup to match? Perfect Corp’s makeup AR takes the guesswork out of online cosmetic shopping. Their hyper-realistic tech lets you do just that with impressive accuracy!

With Perfect Corp’s makeup AR, you get to try before you buy! Play around with different lipsticks, eyeshadows, and more, confident that their advanced color-matching guarantees incredibly realistic results. Struggling to decide if glitter is your style or a subtle matte is more your vibe? Perfect Corp’s AR captures textures beautifully, letting you see exactly how a shimmery shadow or a creamy lipstick will look.

Plus, thanks to its powerful skin tone analysis and lighting adjustments, your virtual makeup trials will seamlessly blend with your new outfit for a complete look.

It’s not just Gucci, Burberry, or ZERO10; the whole fashion industry is waking up to AR. All of the big brands have been investing in AR try-on technology ever since Meta announced their intentions on Metaverse, knowing it reduces returns and makes shopping more fun for customers for any type of retail product.

AR technologies in vogue

The introduction of such machine learning models aligns with a broader surge of interest and investment in augmented reality (AR) and virtual reality (VR) technologies. Market forecasts indicate substantial growth in the coming years, fueled by advancements in hardware, software, and real-world applications.

AR and VR are transforming various industries:

  • Retail: Virtual try-on solutions like ZERO10’s are reducing returns and boosting customer engagement for fashion brands
  • Entertainment: Immersive gaming experiences continue to push the boundaries of interactive entertainment
  • Training and education: AR/VR simulations offer safe, controlled environments for skill development in fields ranging from healthcare to industrial operations
  • Healthcare: VR is used in patient therapy and surgical planning, while AR assists in diagnostics and visualization

This upward trend demonstrates the increasing recognition of AR/VR’s potential to enhance experiences, streamline processes, and open new avenues for innovation.

The recent release of Apple’s Vision Pro headset further accelerates this momentum. The device’s high-precision displays, spatial audio, and advanced sensor technology promise to unlock next-generation AR/VR experiences across the sectors mentioned before.

AR try-on technologies are about to make online shopping a whole lot easier and more fun. Uncertain fits and disappointing colors might just become a thing of the past. The future of fashion truly is at your fingertips!


Featured image credit: vecstock/Freepik.

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The Data-Driven Future of Fashion https://dataconomy.ru/2015/02/20/the-data-driven-future-of-fashion/ https://dataconomy.ru/2015/02/20/the-data-driven-future-of-fashion/#comments Fri, 20 Feb 2015 15:54:51 +0000 https://dataconomy.ru/?p=12113 It’s incredibly common to hear people say that “big data is disrupting every industry”- yet, in many respects, the fashion industry is still playing catch up. Although data science has been used to optimise delivery logistics, recommend products and target customers, it’s yet to disrupt actual fashion products in a profound way. This is where […]]]>

Daina CEO FashionMetricIt’s incredibly common to hear people say that “big data is disrupting every industry”- yet, in many respects, the fashion industry is still playing catch up. Although data science has been used to optimise delivery logistics, recommend products and target customers, it’s yet to disrupt actual fashion products in a profound way. This is where Fashion Metric come in- their SaaS helps businesses gain better bodily measurements from their customers, decreasing returns and increasing customer satisfaction. We recently spoke to FashionMetric CEO & Co-Founder Daina Burnes Linton about the past, present and future of the fashion industry- and where data science comes in.


Briefly introduce yourself and your product. 

My name is Daina Linton and I am the co-founder and CEO of Fashion Metric, a SaaS company that builds technologies for apparel brands and retailers to make it easy for shoppers to buy better fitting clothes both in-store and online.

I grew up in a family that has a history in master tailoring dating back to the early 1900’s with tailor shops in Lithuania, Germany and eventually Canada. I was inspired by my family craft and wanted to find a way to evolve traditional tailoring concepts and attentiveness to body measurements into modern times.

The core of our technology is the Virtual Tailor API, which provides more measurements than a typical tailor would measure in person without actually requiring a person to be physically measured. One of the hardest things to do is to make something very complex look easy to the end-user. While our technology is driven by mathematical algorithms and complex datasets under-the-hood, a shopper only has to answer a few simple questions for our technology to predict over 50 discrete body measurements. This data can be passed through to the retailer to not only better understand their customers but to also leverage the information for a variety of purposes such as making better inventory management decisions.

You started off as a consumer-facing ecommerce store; talk us through your journey, and why you decided to move towards proprietary tech. 

The problem all consumers face when shopping for clothes both in-store and online is determining what size they should buy. In a brick and mortar store shoppers solve this problem by taking a few different sizes into a dressing room. Online they’re forced to either take a risk by buying only one size or pay more upfront to buy multiple sizes and return the size that doesn’t fit.

We initially released the Fashion Metric technology on our own consumer-facing eCommerce apparel store. Instead of selecting a size, shoppers would simply browse based on style and our technology would ascertain the correct size to ship to the customer. Along with off-the-rack sizes (i.e. S, M, L, XL) we also sold custom clothing, all exclusively fitted by the output of our technology.

The results were very encouraging and soon other retailers reached-out requesting access to our technology for use in their stores.  The demand grew a lot faster than we had expected and we quickly realized there was a huge opportunity to license our technology rather than using it exclusively on our store.

Your website claims 28% of apparel bought online is returned- this high number is often linked with poor sizing. Historically speaking, how did off-the-rack sizing get so out of kilter? 

The mass production of clothing based on a standard sizing system began to accelerate by the mid 19th century, mainly driven by the military uniform requirements from the American Civil War and Crimean War. Governments became involved in measuring body dimensions of thousands of recruits to discover body measurement patterns to form the basis of a set of standard sizes that fit most soldiers. This general concept was soon translated to civilian clothing for both men and women by the turn of the century. This era was a transformative time for the apparel industry, where access to garments had been traditionally bespoke or homemade toward the mass production of ready-to-wear sizes that could be purchased and worn straight off the rack.

Over time various sizing standardization systems developed to serve different populations while managing the delicate balance between mass production requirements and customer satisfaction around fit. It became increasingly common for manufacturers to assign their own sizing system resulting in the non-standardized system of ready-to-wear sizing that we know today. This has led to an incredible amount of consumer confusion around ready-to-wear sizing, since a Medium in one brand could be a Small in another. The problem is amplified online, with consumer’s left to puzzle over size charts.

Another (much less tech-centric) to the sizing problem is the rise of the “One Size Fits All” store- what are your thoughts on this? 

While it would be great to think that there is one specific body type that is similar to everyone this just isn’t realistic. It doesn’t take mathematical algorithms to realize that with billions of people on this planet there is an incredibly diversity in body types, shapes, and sizes, not just one.

 In many cases the idea of “One Size Fits All” ends-up being offensive as it can easily make people feel like there is something wrong with them when statistically speaking they are more normal than the model they are comparing themselves to.

We are at such an incredible time in our history, hyper-personalization is finally possible and it’s technologies like the ones we work on every single day that we hope will show people that they are fine just they way they are. Forget one-size-fits-all, let’s talk about appreciating how unique each of us is and how we can find clothes that allows us to be proud and express who we are as individuals.

Big data and ecommerce is a match made in Heaven, but big data and fashion is a pairing we hear a lot less about. Why do you think this is? 

Physical stores have seen massive disruption over the last decade with companies like Amazon.com and Netflix catalyzing major consumer habit changes. Walk down the main street of any major city now and you’ll find lots of restaurants and clothing stores but less and less bookstores and video rental stores.

The shift from physical to digital has swept through entire industries but left apparel relatively untouched. Amazon tipped the scales with books when they introduced the “Look Inside” feature, making it possible for consumers to virtually browse books like they would in a bookstore. Netflix moved people from physical disks to streaming, allowing instant access to content. These were disruptive forces that made it easier for people to do something they had done the same way for a long time.

In the apparel space “fit” has always been the limiting factor, just like people want to browse a book or watch a movie preview, they still want to try clothes on. Despite the growth of technology and access to huge amounts of data, the apparel industry is challenged with providing a compelling experience for consumers so that they can buy clothes without trying them on.

Can you name any other companies at the intersection between fashion and tech whose work particularly excites you? 

I’m particularly excited about the 3D Printing industry and its potential to drastically impact the way clothing is made. It’s still early so it’s hard to name a single leader in the space but the idea of seeing something online and printing it in your living room is likely a closer reality than we might think. Couple this with companies like Oculus that are making it possible to re-create experiences that could normally only happen in a shopping mall and it’s clear we are entering a new era. We are continuously evaluating how our technology can be leveraged not just for where the industry is today but where it is heading.

What’s in the roadmap for the future of Fashion Metric? 

We see a future where apparel brands and retailers know more about their shoppers than ever before. To power these experiences we are always looking for ways to collect more data and algorithms to help make this data more meaningful and actionable.

You can expect to see Fashion Metric come out with products that run behind-the-scenes with retailers both in-store and online to enhance the end-to-end shopping experience. You might not know we are there, but that’s the beauty in what we do. Our goal is to build technologies that shoppers might not even know they are using but that personalizes their experience in a way that absolutely delights them.

What do you envision in the future of data science & ecommerce in general? 

There is no doubt that mobile will be one of the single largest forces driving changes and innovation in the eCommerce world. This directly impacts data science as the medium that people use to shop moves from a personal computer to a personal phone. Your smartphone has a lot more data on it about you than your computer does and leveraging this data will change the data science world forever.

Back in the late 1990’s consumers were terrified of cookies. The idea that a website would track what they do was an uncomfortable and foreign concept. Now every single eCommerce website uses cookies to personalize the experience and consumers have become very comfortable with the concept after realizing and enjoying the benefits that it provides. The same thing is happening with smartphones and it’s happening at a fast pace. More apps than ever now ask for location data and consumers are getting more comfortable sharing this and more data to help provide a more personalized experience.


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Data Science: Building Better Bras https://dataconomy.ru/2014/06/11/data-science-building-better-bras/ https://dataconomy.ru/2014/06/11/data-science-building-better-bras/#respond Wed, 11 Jun 2014 09:11:00 +0000 https://dataconomy.ru/?p=5421 Tailored retail experiences are one of the most well-known applications of big data. We have premium streaming sites that know what you want to watch next better than you do; book vendors which can accurately map your literary tastes; and now, an e-commerce lingerie startup which knows if you suffer from strap slippages or uncomfortable […]]]>

Tailored retail experiences are one of the most well-known applications of big data. We have premium streaming sites that know what you want to watch next better than you do; book vendors which can accurately map your literary tastes; and now, an e-commerce lingerie startup which knows if you suffer from strap slippages or uncomfortable underwire- and also has the perfect bra to combat these problems.

Even if you’re not in possession of breasts yourself, it’s unlikely you haven’t encountered someone wrestling with an errant strap, or discretely trying to push up or readjust. The problem isn’t badly made bras; the problem is there are so many different types of body shape that rib cage and cup size alone don’t tell the whole story. This is something that True&Co, who have currently identified over 6,000 different body shapes, is very familiar with.

In the beginning, True&Co started out as a bra recommender. First-time users would take a two-minute quiz, telling True&Co if their bras were too tight, or if they had problems with “busting out” (apparently 62% of women do), and True&Co would use these metrics to recommend bras for a customer’s particular body shape. Now, they’re using the 7 million data points they’ve accrued to design bras tailored to their users’ body shapes. As founder Michelle Lam states: “With all this virtual stuff, it’s so easy to create a uniquely personal experience for every person, but creating physical goods that also feel like they’re made for you is what’s incredibly fascinating to me.”

The bras, using a patented fitting system called True Spectrum, are variable far beyond the usual remit of chest width and cup size. They take into accont if a customer’s breasts are full or shallow, high or low, wide-set or close together. These bras have quickly become True&Co’s bestselling products, accounting for a quarter of all sales and boosting revenue 600% in the past few months.

Victoria’s Secret have also established a quiz for their clients, and startup ThirdLove have developed a body scanning app for getting measurements. But in the future, we may see tailored fashion moving beyond the chest region. Many have fallen fowl to buying an item of clothing over the internet and immediately returning it, realising it doesn’t look half as good on their body shape as it does on the model. Tailored clothing recommendations could change this, something that Lam is aware of: “I look at the old retailers out there, and I see an imperfect model,” she says. “I think this is the way women are going to shop for intimate apparel in the future, and not only that, but I really believe this is the way women will shop for all apparel in the future.”

Read more here.
(Photo credit: Melissa Maples)



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