Real-Time Face Tracking for Audience Engagement

Chengyuan Peng; Sari Järvinen; Johannes Peltola

Real-Time Face Tracking for Audience Engagement

Chengyuan Peng, Sari Järvinen, Johannes Peltola

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-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 language	English
Title of host publication	Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science (EECSS'16)
Number of pages	4
Publication status	Published - 2016
MoE publication type	A4 Article in a conference publication
Event	2nd World Congress on Electrical Engineering and Computer Systems and Science, EECSS'16 - Budapest, Hungary Duration: 16 Aug 2016 → 17 Aug 2016

Conference

Conference	2nd World Congress on Electrical Engineering and Computer Systems and Science, EECSS'16
Abbreviated title	EECSS'16
Country	Hungary
City	Budapest
Period	16/08/16 → 17/08/16

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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) http://www.avestia.com/EECSS2016_Proceedings/files/paper/MVML/105.pdf

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title = "Real-Time Face Tracking for Audience Engagement",

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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",

booktitle = "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 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. <http://www.avestia.com/EECSS2016_Proceedings/files/paper/MVML/105.pdf>

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AU - Peng, Chengyuan

AU - Järvinen, Sari

AU - Peltola, Johannes

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - face tracking

KW - face detection

KW - 3D face anthropometry

KW - pose estimation

KW - camera calibration

M3 - Conference article in proceedings

SN - 978-1-927877-25-8

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

T2 - 2nd World Congress on Electrical Engineering and Computer Systems and Science, EECSS'16

Y2 - 16 August 2016 through 17 August 2016

ER -

Access to Document

http://www.avestia.com/EECSS2016_Proceedings/files/paper/MVML/105.pdf