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.
Hugh J. Paterson III (2014) Keyboard layouts: Lessons from the Meꞌphaa and Sochiapam Chinantec designs. In: Endangered Languages and New Technologies edited by Mari C. Jones. pp. 49-66. Cambridge University Press.