Improved hierarchical clustering for face images in videos: Integrating positional and temporal information with HAC

Subhradeep Kayal*

*Corresponding author for this work

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

    4 Citations (Scopus)

    Abstract

    Efficient techniques for face clustering, along with speech and text recognition, can provide the means for rapid browsing and accurate retrieval of videos from large video databases. Observing that video data contains information about not only the face features, but also the temporal ordering of the faces and positional coordinates of the face-regions within the video frame, an attempt is made to consolidate all of these details into the framework of the flexible and intuitive hierarchical clustering algorithm. This paper outlines a novel initialization mechanism for the hierarchical clustering to follow, based on the temporal and positional information of the face-samples extracted from a video. Experiments with news broadcast videos show that the novel algorithm is considerably more efficient than it's parent, and is promising for future exploration.

    Original languageEnglish
    Title of host publicationICMR 2014 - Proceedings of the ACM International Conference on Multimedia Retrieval 2014
    PublisherACM
    Pages455-458
    Number of pages4
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    EventACM International Conference on Multimedia Retrieval - Glasgow, United Kingdom
    Duration: 1 Apr 20144 Apr 2014
    Conference number: 4

    Conference

    ConferenceACM International Conference on Multimedia Retrieval
    Abbreviated titleICMR
    CountryUnited Kingdom
    CityGlasgow
    Period01/04/201404/04/2014

    Keywords

    • Face clustering
    • Hierarchical clustering

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