Mobile visual clothing search


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.

In International Conference on Multimedia and Expo Workshops (ICMEW), IEEE.
George Cushen
George Cushen
A Data Scientist & Product Enthusiast

I’m a data scientist passionate about conversational AI, augmented/virtual reality, and knowledge graphs. In my spare time, I enjoy CrossFit and open source. Follow me on twitter to be notified of new content.