• DocumentCode
    720722
  • Title

    Robust visual analysis for planogram compliance problem

  • Author

    Saran, Anurag ; Hassan, Ehtesham ; Maurya, Avinash Kumar

  • Author_Institution
    Cadence Design Syst., India
  • fYear
    2015
  • fDate
    18-22 May 2015
  • Firstpage
    576
  • Lastpage
    579
  • Abstract
    This paper presents a novel visual analysis based framework for automated planogram compliance check in retail stores. Our framework provides an efficient and convenient solution for ensuring planogram compliance by real-time analysis of the shelf image acquired in freehand manner. We present a novel application of Hausdorff metric for occupancy computation in product shelf images. Subsequently, we present a robust solution for product counting which applies robust row detection algorithm, and exploits texture and color feature for accurate counting. In this context, our system addresses the most general scenario of multiple varieties in single product type. The empirical validation of our framework is demonstrated on range of real-life images from stores located across different geographies, where it has achieved satisfactory and encouraging results.
  • Keywords
    feature extraction; image colour analysis; real-time systems; Hausdorff metric; automated planogram compliance check; color feature; geography; occupancy computation; planogram compliance problem; product counting; product shelf images; real-time analysis; retail stores; robust row detection; robust solution; robust visual analysis; texture feature; Accuracy; Feature extraction; Histograms; Image color analysis; Measurement; Robustness; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision Applications (MVA), 2015 14th IAPR International Conference on
  • Conference_Location
    Tokyo
  • Type

    conf

  • DOI
    10.1109/MVA.2015.7153257
  • Filename
    7153257