Recommendation System for Outfit Selection (RSOS)

نویسندگان

  • Shiv H. Sutar
  • Akshata H. Khade
چکیده

We propose a system which will be able to recommend the user to choose appropriate outfits suits to their personality. The necessity of this system is to reduce the outfit selection and purchasing time; this will also help to create tailor made outfits as per the personality traits. The guidelines for selection of their respective outfits are based upon various bodily parameters that evolve with the learning of available labeled and unlabeled data. The system is based on two modules of processes; first one is to recognize the features for usage of outfits like traditional, western, functional, daytime or night etc, second is to calculate the body measurement parameters. The proposed system will have image capturing by using HAAR feature or input device for getting body parameters. We intend to classify and extract the best possible outfits from the system by using HIGEN MINER algorithm. The applications of outfit selection will be ranging from manual gender selection, image processing with body feature extractions, Value comparison with database by using different statistical techniques and data mining algorithms. After that it will recommend best outfits as per body parameters, inputs and availability

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عنوان ژورنال:
  • CoRR

دوره abs/1402.6692  شماره 

صفحات  -

تاریخ انتشار 2014