Dataset issues in object recognition

J. Ponce, T. L. Berg, M. Everingham, D. A. Forsyth, M. Hebert, S. Lazebnik, M. Marszalek, C. Schmid, B. C. Russell, A. Torralba, C. K. I. Williams, J. Zhang, A. Zisserman

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. Current datasets are lacking in several respects, and this paper discusses some of the lessons learned from existing efforts, as well as innovative ways to obtain very large and diverse annotated datasets. It also suggests a few criteria for gathering future datasets.
    Original languageEnglish
    Title of host publicationToward category-level object recognition
    EditorsJean Ponce, Martial Hebert, Cordelia Schmid, Andrew Zisserman
    Place of PublicationBerlin
    PublisherSpringer
    Pages29-48
    Number of pages20
    ISBN (Electronic)9783540687955
    ISBN (Print)9783540687948
    DOIs
    Publication statusPublished - 2006

    Publication series

    NameLecture notes in computer science
    PublisherSpringer
    Volume4170
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

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    Object recognition

    Cite this

    Ponce, J., Berg, T. L., Everingham, M., Forsyth, D. A., Hebert, M., Lazebnik, S., ... Zisserman, A. (2006). Dataset issues in object recognition. In J. Ponce, M. Hebert, C. Schmid, & A. Zisserman (Eds.), Toward category-level object recognition (pp. 29-48). (Lecture notes in computer science; Vol. 4170). Berlin: Springer . https://doi.org/10.1007/11957959_2
    Ponce, J. ; Berg, T. L. ; Everingham, M. ; Forsyth, D. A. ; Hebert, M. ; Lazebnik, S. ; Marszalek, M. ; Schmid, C. ; Russell, B. C. ; Torralba, A. ; Williams, C. K. I. ; Zhang, J. ; Zisserman, A. / Dataset issues in object recognition. Toward category-level object recognition. editor / Jean Ponce ; Martial Hebert ; Cordelia Schmid ; Andrew Zisserman. Berlin : Springer , 2006. pp. 29-48 (Lecture notes in computer science).
    @inbook{3d43eff28e424f2eb915109314465fc9,
    title = "Dataset issues in object recognition",
    abstract = "Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. Current datasets are lacking in several respects, and this paper discusses some of the lessons learned from existing efforts, as well as innovative ways to obtain very large and diverse annotated datasets. It also suggests a few criteria for gathering future datasets.",
    author = "J. Ponce and Berg, {T. L.} and M. Everingham and Forsyth, {D. A.} and M. Hebert and S. Lazebnik and M. Marszalek and C. Schmid and Russell, {B. C.} and A. Torralba and Williams, {C. K. I.} and J. Zhang and A. Zisserman",
    note = "This book is the outcome of two workshops that were held in Taormina in 2003 and 2004.",
    year = "2006",
    doi = "10.1007/11957959_2",
    language = "English",
    isbn = "9783540687948",
    series = "Lecture notes in computer science",
    publisher = "Springer",
    pages = "29--48",
    editor = "Jean Ponce and Martial Hebert and Cordelia Schmid and Zisserman, {Andrew }",
    booktitle = "Toward category-level object recognition",

    }

    Ponce, J, Berg, TL, Everingham, M, Forsyth, DA, Hebert, M, Lazebnik, S, Marszalek, M, Schmid, C, Russell, BC, Torralba, A, Williams, CKI, Zhang, J & Zisserman, A 2006, Dataset issues in object recognition. in J Ponce, M Hebert, C Schmid & A Zisserman (eds), Toward category-level object recognition. Lecture notes in computer science, vol. 4170, Springer , Berlin, pp. 29-48. https://doi.org/10.1007/11957959_2

    Dataset issues in object recognition. / Ponce, J.; Berg, T. L.; Everingham, M.; Forsyth, D. A.; Hebert, M.; Lazebnik, S.; Marszalek, M.; Schmid, C.; Russell, B. C.; Torralba, A.; Williams, C. K. I.; Zhang, J.; Zisserman, A.

    Toward category-level object recognition. ed. / Jean Ponce; Martial Hebert; Cordelia Schmid; Andrew Zisserman. Berlin : Springer , 2006. p. 29-48 (Lecture notes in computer science; Vol. 4170).

    Research output: Chapter in Book/Report/Conference proceedingChapter

    TY - CHAP

    T1 - Dataset issues in object recognition

    AU - Ponce, J.

    AU - Berg, T. L.

    AU - Everingham, M.

    AU - Forsyth, D. A.

    AU - Hebert, M.

    AU - Lazebnik, S.

    AU - Marszalek, M.

    AU - Schmid, C.

    AU - Russell, B. C.

    AU - Torralba, A.

    AU - Williams, C. K. I.

    AU - Zhang, J.

    AU - Zisserman, A.

    N1 - This book is the outcome of two workshops that were held in Taormina in 2003 and 2004.

    PY - 2006

    Y1 - 2006

    N2 - Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. Current datasets are lacking in several respects, and this paper discusses some of the lessons learned from existing efforts, as well as innovative ways to obtain very large and diverse annotated datasets. It also suggests a few criteria for gathering future datasets.

    AB - Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. Current datasets are lacking in several respects, and this paper discusses some of the lessons learned from existing efforts, as well as innovative ways to obtain very large and diverse annotated datasets. It also suggests a few criteria for gathering future datasets.

    U2 - 10.1007/11957959_2

    DO - 10.1007/11957959_2

    M3 - Chapter

    SN - 9783540687948

    T3 - Lecture notes in computer science

    SP - 29

    EP - 48

    BT - Toward category-level object recognition

    A2 - Ponce, Jean

    A2 - Hebert, Martial

    A2 - Schmid, Cordelia

    A2 - Zisserman, Andrew

    PB - Springer

    CY - Berlin

    ER -

    Ponce J, Berg TL, Everingham M, Forsyth DA, Hebert M, Lazebnik S et al. Dataset issues in object recognition. In Ponce J, Hebert M, Schmid C, Zisserman A, editors, Toward category-level object recognition. Berlin: Springer . 2006. p. 29-48. (Lecture notes in computer science). https://doi.org/10.1007/11957959_2