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Mirrorsize US to launch ‘draping’ solution based on customer’s selection of fabric, style

Mirrorsize US to launch draping solution based on customers selection of fabric style 002The Indian arm of NJ-based company, Mirrorsize US Inc, plans to launch a ‘Draping’ product in the next three to four months. “Based on customer’s selection of fabric, style, etc, we will sew the apparel to drape it on the person on his/her mobile to give real life visualisation and enrich customer experience,” says Arup Chakraborty, Founder and CEO, of the company. Also on the cards is style recommendation. This will depend on getting funding from a brand. Style recommendation will be based on customer’s style preferences, “We will use deep learning to recommend styles to a customer by geography,” he explains.

The company currently offers MD GetMeasured – for bespoke merchants to get precise body measurement of their customers and MS Size2Fit for merchants selling readymade apparels, “where our product will give precise size recommendation to a customer by brand, by apparel and by apparel category. Shirts are available as regular, slim and casual fit,” adds Chakraborty

Solution to solve sizing issues

Chakraborty points out sometimes online returns are as high as 55 per cent, predominantly due to ill-fit. There is noMirrorsize US to launch draping solution based on customers selection of fabric style 001 technology available to get precise human body measurement which prompted them to introduce a solution that cannot only solve ‘sizing’ and ‘personalisation’ issues but also remove supply chain inefficiencies and help scale enterprises by making business more seamless. “This device requires no additional hardware/investment and works on any smartphone and tablet. Users can get their precise body measurement, real-time in seconds. We create a 3D model on the run-time and deform the 3D model to take the shape of the object,” informs Chakraborty.

Independent of background and light

The solution can work with both cluttered and uncluttered background. It is independent of the side pose and can identify another human. It also works in low light. “We generate 3D model of the object on the run-time and deform the 3D model to the shape of the object,” he adds. Drawing a comparison with Michael Black from MPI Germany, known to be the guru of 3D mesh who developed a similar technology to deform a 3D mesh from two images, Chakraborty notes, “Black formed a company called Bodylabs.com and after R&D for over two years, filled his paper claiming accuracy of 8-10 cm. Bodylabs was acquired by Amazon in 2017. Our accuracy is <1 CM and we’re in the process of filing our paper at IEEE in early 2019,”he explains.

Robust plans ahead

Though users can wear both tight and loose fitting garments, the company prefers them to wear tight fitted cloths for accurate results. “We use Physics, Simulation, FEM, Computer Graphics etc. to drape our user. It’s an enterprise SaaS model, which will allow brands, retailers and institutions to use our product,” Chakraborty avers. The company plans to roll-out GTM strategy in Q1’19 and expects to hit $30 million in global revenue (SaaS) in FY 2019-20 as per US GAAP. 

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