Detecting people using mutually consistent poselet activations
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Describing people: A poselet-based approach to attribute classification
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Hi, magic closet, tell me what to wear!
Proceedings of the 20th ACM international conference on Multimedia
Towards decrypting attractiveness via multi-modality cues
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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In this demo, we present a practical system, magic closet, for automatic occasion-oriented clothing pairing. Given a user-input occasion, e.g., wedding or shopping, the magic closet intelligently and automatically pairs the user-specified reference clothing (upper-body or lower-body) with the most suitable one from online shops. Two key criteria are explicitly considered for the magic closet system. One criterion is to wear properly, e.g., compared to suit pants, it is more decent to wear a cocktail dress for a banquet occasion. The other criterion is to wear aesthetically, e.g., a red T-shirt matches better white pants than green pants. To narrow the semantic gap between the low-level visual features and the high-level occasion categories, we propose to adopt middle-level clothing attributes (e.g., clothing category, color, pattern) as a bridge. More specifically, the clothing attributes are treated as latent variables in our proposed latent Support Vector Machine (SVM) based recommendation model. The wearing properly criterion is described through a feature-occasion potential and an attribute-occasion potential, while the wearing aesthetically criterion is expressed by an attribute-attribute potential.