Fashion Coordinates Recommender System Using Photographs from Fashion Magazines

Fashion magazines contain a number of photographs of fashion models, and their clothing coordinates serve as useful references. In this paper, we propose a recommender system for clothing coordinates using full-body photographs from fashion magazines. The task is that, given a photograph of a fashion item (e.g. tops) as a query, to recommend a photograph of other fashion items (e.g. bottoms) that is appropriate to the query. With the proposed method, we use a probabilistic topic model for learning information about coordinates from visual features in each fashion item region. We demonstrate the effectiveness of the proposed method using real photographs from a fashion magazine and two fashion style sharing services with the task of making top (bottom) recommendations given bottom (top) photographs.

[1]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[2]  Mounia Lalmas,et al.  SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval , 2006 .

[3]  Naonori Ueda,et al.  Modeling Social Annotation Data with Content Relevance using a Topic Model , 2009, NIPS.

[4]  Henry Lieberman,et al.  What am I gonna wear?: scenario-oriented recommendation , 2007, IUI '07.

[5]  T. Minka.  Estimating a Dirichlet distribution , 2012 .

[6]  N. Stanietsky,et al.  The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity , 2009, Proceedings of the National Academy of Sciences.

[7]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[8]  O. Bagasra,et al.  Proceedings of the National Academy of Sciences , 1914, Science.

[9]  Michael I. Jordan,et al.  Modeling annotated data , 2003, SIGIR.

[10]  Andrew McCallum,et al.  Polylingual Topic Models , 2009, EMNLP.

[11]  Refractor.  Vision , 2000, The Lancet.

[12]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[13]  Michael I. Jordan,et al.  Advances in Neural Information Processing Systems 30 , 1995 .

[14]  Thomas Hofmann,et al.  Collaborative filtering via gaussian probabilistic latent semantic analysis , 2003, SIGIR.

[15]  Bernt Schiele,et al.  Pictorial structures revisited: People detection and articulated pose estimation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Takeo Kanade,et al.  Neural Network-Based Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[18]  Thomas Hofmann,et al.  Probabilistic Latent Semantic Analysis , 1999, UAI.

[19]  Li Fei-Fei,et al.  Spatially coherent latent topic model for concurrent object segmentation and classification , 2007 .

[20]  J. Meigs,et al.  WHO Technical Report , 1954, The Yale Journal of Biology and Medicine.

[21]  Yoshio Nakatani,et al.  Fashion Support from Clothes with Characteristics , 2009, HCI.

[22]  Susan T. Dumais,et al.  Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval , 2004, SIGIR 2004.

[23]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[24]  Deva Ramanan,et al.  Learning to parse images of articulated bodies , 2006, NIPS.

[25]  Mark Steyvers,et al.  Finding scientific topics , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[26]  H. Damasio,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence: Special Issue on Perceptual Organization in Computer Vision , 1998 .

[27]  Naonori Ueda,et al.  Topic Tracking Model for Analyzing Consumer Purchase Behavior , 2009, IJCAI.

[28]  S. TAKAHASHI,et al.  MIRROR APPLIANCE: RECOMMENDATION OF CLOTHES COORDINATION IN DAILY LIFE , 2008 .