Real-Time Face Tracking for Audience Engagement

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

    Abstract

    Audience measurement is an application area where face tracking and analysis could automatically provide reliable answers about how consumers and users behave spontaneously in real environments. The solutions can detect age, gender, size of the audience, distance from a display, dwell times and more. By knowing audience emotional reactions and engagement towards the products, content
    and campaigns, one can offer audience an improved experience and customized content addressing their interests and behaviour. In this paper, we present a pose-invariant face tracking method to automatically monitor audience’s attention time in real-time. The current system can handle 3D pose variation up to ±55 in yaw and ±30 in pitch angles.
    Original languageEnglish
    Title of host publicationProceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16)
    Number of pages4
    Publication statusPublished - 2016
    MoE publication typeA4 Article in a conference publication
    Event2nd World Congress on Electrical Engineering and Computer Systems and Science, EECSS'16 - Budapest, Hungary
    Duration: 16 Aug 201617 Aug 2016

    Conference

    Conference2nd World Congress on Electrical Engineering and Computer Systems and Science, EECSS'16
    Abbreviated titleEECSS'16
    CountryHungary
    CityBudapest
    Period16/08/1617/08/16

    Fingerprint

    Display devices

    Keywords

    • face tracking
    • face detection
    • 3D face anthropometry
    • pose estimation
    • camera calibration

    Cite this

    Peng, C., Järvinen, S., & Peltola, J. (2016). Real-Time Face Tracking for Audience Engagement. In Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16)
    Peng, Chengyuan ; Järvinen, Sari ; Peltola, Johannes. / Real-Time Face Tracking for Audience Engagement. Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16) . 2016.
    @inproceedings{1766d3820580464aa6448bf5fc2f4acb,
    title = "Real-Time Face Tracking for Audience Engagement",
    abstract = "Audience measurement is an application area where face tracking and analysis could automatically provide reliable answers about how consumers and users behave spontaneously in real environments. The solutions can detect age, gender, size of the audience, distance from a display, dwell times and more. By knowing audience emotional reactions and engagement towards the products, contentand campaigns, one can offer audience an improved experience and customized content addressing their interests and behaviour. In this paper, we present a pose-invariant face tracking method to automatically monitor audience’s attention time in real-time. The current system can handle 3D pose variation up to ±55 in yaw and ±30 in pitch angles.",
    keywords = "face tracking, face detection, 3D face anthropometry, pose estimation, camera calibration",
    author = "Chengyuan Peng and Sari J{\"a}rvinen and Johannes Peltola",
    year = "2016",
    language = "English",
    isbn = "978-1-927877-25-8",
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    Peng, C, Järvinen, S & Peltola, J 2016, Real-Time Face Tracking for Audience Engagement. in Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16) . 2nd World Congress on Electrical Engineering and Computer Systems and Science, EECSS'16, Budapest, Hungary, 16/08/16.

    Real-Time Face Tracking for Audience Engagement. / Peng, Chengyuan; Järvinen, Sari; Peltola, Johannes.

    Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16) . 2016.

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

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    AU - Järvinen, Sari

    AU - Peltola, Johannes

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    KW - face detection

    KW - 3D face anthropometry

    KW - pose estimation

    KW - camera calibration

    M3 - Conference article in proceedings

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    BT - Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16)

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    Peng C, Järvinen S, Peltola J. Real-Time Face Tracking for Audience Engagement. In Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16) . 2016