OVERLAY UPPER CLOTHING TEXTURES TO STILL IMAGES BASED ON HUMAN POSE ESTIMATION
Keywords:
Articulated human pose estimation, virtual clothing, texture mapping, morphingAbstract
The authors propose a system to enhance user’s experience in virtual shopping with image processing techniques. Our proposed system allows a user to submit his or her upright photo taken by any regular camera and choose a product interactively, and then the system returns an output image, which is morphed with upper clothing textures corresponding to the human pose estimated from the given photo. Our approach is based on the result of estimating upper human pose to calculate similarity scores between pairs of image poses and our simple yet efficient method to scale a texture image of an upper clothing product to an appropriate size for morphing. From our study on various magazines and websites of fashion, we define 16 common types of human poses. We create a dataset with 390 photos taken in studios for many products in various poses which cover the 16 defined common poses to train and test our proposed virtual dressing room. Experiments with 12 volunteers to evaluate 150 result images from 50 user images in our system show that 89% of the overlaid output images of the system have good evaluation results. Our proposed system not only enhances users’ experience but also helps users save time with a virtual dressing system before they decide to purchase upper clothing products.
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