Research

Video scene categorization by 3D hierarchical histogram matching


Reference:

Gupta, P., Arrabolu, S. S., Brown, M. and Savarese, S., 2009. Video scene categorization by 3D hierarchical histogram matching. In: ICCV 2009: IEEE 12th International Conference on Computer Vision, 2009-09-29 - 2009-10-02, Kyoto.

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    Official URL:

    http://dx.doi.org/10.1109/ICCV.2009.5459373

    Abstract

    In this paper we present a new method for categorizing video sequences capturing different scene classes. This can be seen as a generalization of previous work on scene classification from single images. A scene is represented by a collection of 3D points with an appearance based codeword attached to each point. The cloud of points is recovered by using a robust SFM algorithm applied on the video sequence. A hierarchical structure of histograms located at different locations and at different scales is used to capture the typical spatial distribution of 3D points and codewords in the working volume. The scene is classified by SVM equipped with a histogram matching kernel, similar to [21, 10, 16]. Results on a challenging dataset of 5 scene categories show competitive classification accuracy and superior performance with respect to a state-of-the-art 2D pyramid matching methods [16] applied to individual image frames.

    Details

    Item Type Conference or Workshop Items (Paper)
    CreatorsGupta, P., Arrabolu, S. S., Brown, M. and Savarese, S.
    DOI10.1109/ICCV.2009.5459373
    DepartmentsFaculty of Science > Computer Science
    Publisher StatementBrown_iccv_2009.pdf: © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
    RefereedYes
    StatusPublished
    ID Code26113

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