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Interactive Product Search Based on Global and Local Visual-Semantic Features

  • Tomáš Skopal
  • Ladislav PeškaEmail author
  • Tomáš Grošup
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11223)

Abstract

In this paper, we present a prototype web application of a product search engine of a fashion e-shop. Today, e-shop product metadata consist of text description, simple attributes (price, size, color, fabric, etc.) and visual information (product photo). Search engines used in e-shops mostly provide text and attribute/category interface for product filtering. In our model, we focus on the visual information applied in an interactive query-by-example scenario. The global visual descriptors may be often ambiguous and may not correspond well with the intended mental query of the user. Therefore, we proposed and evaluated model and GUI allowing user to guide the query process by selecting image regions (patches) of interest within the query. In the demo evaluation, we show that allowing user to specify relevant image patches led to a significant improvement of the results’ relevance in the vast majority of tested queries.

Notes

Acknowledgments

This research has been supported by Czech Science Foundation (GAČR) project Nr. 17-22224S.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Tomáš Skopal
    • 1
  • Ladislav Peška
    • 1
    Email author
  • Tomáš Grošup
    • 1
  1. 1.Faculty of Mathematics and Physics, SIRET Research GroupCharles UniversityPragueCzech Republic

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