Choosing which Clothes to Wear Confidently: A Tool for Pattern Matching

This work attempts to make a first step in computationally determining whether a pair of clothes, in this case of a tie and a shirt, can be worn together or not, based on the current social norms of color-matching. Our aim is to give visually impaired persons the ability, using snapshots taken by their mobile phones, to independently and confidently be able to choose from their wardrobe which set of clothes they can wear together. Given a sample of 41 pairs of shirts and corresponding matching ties of 74 pixels squared and using a color-histogram of 8 bins, we show that with Ridge Regression we can achieve a 10-fold cross-validation classification error of 0.175, with a standard neural network with 10 hidden neurons a 10fold cross-validation classification error of 0.05 and with a Siamese neural network an accuracy of only 0.33.