Mobile visual clothing search

Abstract

We present a mobile visual clothing search system whereby a smart phone user can either choose a social networking photo or take a new photo of a person wearing clothing of interest and search for similar clothing in a retail database. From the query image, the person is detected, clothing is segmented, and clothing features are extracted and quantized. The information is sent from the phone client to a server, where the feature vector of the query image is used to retrieve similar clothing products from online databases. The phone’s GPS location is used to re-rank results by retail store location. State of the art work focuses primarily on the recognition of a diverse range of clothing offline and pays little attention to practical applications. Evaluated on a challenging dataset, the system is relatively fast and achieves promising results.

Publication
In International Conference on Multimedia and Expo Workshops (ICMEW), IEEE.
George Cushen
George Cushen
Data Science Leader, PhD

I’m a data science leader passionate about conversational AI, augmented/virtual reality, and Graph AI. In my spare time, I enjoy CrossFit and open source. Follow me on Twitter and Instagram to be notified of new content.