Mobile product image search by automatic query object extraction

Xiaohui Shen*, Zhe Lin, Jonathan Brandt, Ying Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

31 Scopus citations


Mobile product image search aims at identifying a product, or retrieving similar products from a database based on a photo captured from a mobile phone camera. Application of traditional image retrieval methods (e.g. bag-of-words) to mobile visual search has been shown to be effective in identifying duplicate/near-duplicate photos, near-planar and textured objects such as landmarks, books/cd covers. However, retrieving more general product categories is still a challenging research problem due to variations in viewpoint, illumination, scale, the existence of blur and background clutter in the query image, etc. In this paper, we propose a new approach that can simultaneously extract the product instance from the query, identify the instance, and retrieve visually similar product images. Based on the observation that good query segmentation helps improve retrieval accuracy and good search results provide good priors for segmentation, we formulate our approach in an iterative scheme to improve both query segmentation and retrieval accuracy. To this end, a weighted object mask voting algorithm is proposed based on a spatially-constrained model, which allows robust localization and segmentation of the query object, and achieves significantly better retrieval accuracy than previous methods. We show the effectiveness of our approach by applying it to a large, real-world product image dataset and a new object category dataset.

Original languageEnglish (US)
Title of host publicationComputer Vision, ECCV 2012 - 12th European Conference on Computer Vision, Proceedings
Number of pages14
EditionPART 4
StatePublished - 2012
Event12th European Conference on Computer Vision, ECCV 2012 - Florence, Italy
Duration: Oct 7 2012Oct 13 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume7575 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other12th European Conference on Computer Vision, ECCV 2012

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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