Interactive object counting

Carlos Arteta, Victor Lempitsky, J. Alison Noble, Andrew Zisserman

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    98 Citations (Scopus)


    Our objective is to count (and localize) object instances in an image interactively. We target the regime where individual object detectors do not work reliably due to crowding, or overlap, or size of the instances, and take the approach of estimating an object density. Our main contribution is an interactive counting system, along with solutions for its main components. Thus, we develop a feature vocabulary that can be efficiently learnt on-the-fly as a user provides dot annotations - this enables densities to be generated in an interactive system. Furthermore, we show that object density can be estimated simply, accurately and efficiently using ridge regression - this matches the counting accuracy of the much more costly learning-to-count method. Finally, we propose two novel visualization methods for region counts that are efficient and effective - these enable integral count regions to be displayed to quickly determine annotation points for relevance feedback. The interactive system is demonstrated on a variety of visual material, including photographs, microscopy and satellite images.

    Original languageEnglish
    Title of host publicationComputer Vision, ECCV 2014 - 13th European Conference, Proceedings
    PublisherSpringer Verlag
    Number of pages15
    EditionPART 3
    ISBN (Print)9783319105772
    Publication statusPublished - 2014
    Event13th European Conference on Computer Vision, ECCV 2014 - Zurich, Switzerland
    Duration: 6 Sep 201412 Sep 2014

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 3
    Volume8691 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference13th European Conference on Computer Vision, ECCV 2014


    • biomedical image analysis
    • Interactive vision systems
    • object counting
    • relevance feedback
    • visual recognition


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