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Signature quadratic form distances for content-based similarity

Published: 19 October 2009 Publication History

Abstract

Determining similarity is a fundamental task in querying multimedia databases in a content-based way. For this challenging task, there exist numerous similarity models which measure the similarity among objects by using their contents. In order to cope with voluminous multimedia data, similarity models are supposed to be both effective and efficient. To this end, we introduce the Signature Quadratic Form Distance measure which allows efficient similarity computations based on flexible feature representations. Our new approach bridges the gap between the well-known concept of Quadratic Form Distances and feature signatures. Experimentation indicates that our similarity measure is able to compete with state-of-the-art similarity models regarding effectiveness of content-based similarity search. Moreover, our Signature Quadratic Form Distance outperforms the established Earth Mover's Distance in efficiency: we obtain a speed-up factor of greater than 50.

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    cover image ACM Conferences
    MM '09: Proceedings of the 17th ACM international conference on Multimedia
    October 2009
    1202 pages
    ISBN:9781605586083
    DOI:10.1145/1631272
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 19 October 2009

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    Author Tags

    1. content-based similarity search
    2. feature signatures
    3. quadratic form distance

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    MM09
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    MM09: ACM Multimedia Conference
    October 19 - 24, 2009
    Beijing, China

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    Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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    • (2024)nSimplex Zen: A Novel Dimensionality Reduction for Euclidean and Hilbert SpacesACM Transactions on Knowledge Discovery from Data10.1145/364764218:6(1-44)Online publication date: 12-Apr-2024
    • (2021)Convolution operations for relief-pattern retrieval, segmentation and classification on mesh manifoldsPattern Recognition Letters10.1016/j.patrec.2020.11.017142:C(32-38)Online publication date: 1-Feb-2021
    • (2020)Representing and analyzing relief patterns using LBP variants on mesh manifoldPattern Analysis and Applications10.1007/s10044-020-00920-6Online publication date: 21-Sep-2020
    • (2019)Ptolemaic Indexing for Managing and Querying Internet of Things (IoT) Data2019 IEEE International Conference on Big Data (Big Data)10.1109/BigData47090.2019.9005725(4148-4151)Online publication date: Dec-2019
    • (2019)Defining Mesh-LBP Variants for 3D Relief Patterns ClassificationCommunications, Signal Processing, and Systems10.1007/978-3-030-19816-9_12(151-166)Online publication date: 5-May-2019
    • (2018)Three Precise Spatial Signatures for Image Copy Recall2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE)10.1109/CCECE.2018.8447689(1-5)Online publication date: May-2018
    • (2018)FAST: Rapid determinations of antibiotic susceptibility phenotypes using label‐free cytometryCytometry Part A10.1002/cyto.a.2337093:6(639-648)Online publication date: 7-May-2018
    • (2017)Retrieval of surfaces with similar relief patternsProceedings of the Workshop on 3D Object Retrieval10.2312/3dor.20171058(95-103)Online publication date: 23-Apr-2017
    • (2017)Point-cloud shape retrieval of non-rigid toysProceedings of the Workshop on 3D Object Retrieval10.2312/3dor.20171056(75-84)Online publication date: 23-Apr-2017
    • (2017)Scalable 3D shape retrieval using local features and the signature quadratic form distanceThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-016-1301-533:12(1571-1585)Online publication date: 1-Dec-2017
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