User's Gaze Tracking System and Its Application Using Head Pose Estimation

Hyunduk Kim; Myoung Kyu Sohn; Dong Ju Kim; Nuri Ryu

doi:10.1109/AIMS.2014.48

User's Gaze Tracking System and Its Application Using Head Pose Estimation

Hyunduk Kim, Myoung Kyu Sohn, Dong Ju Kim, Nuri Ryu

Division of Automotive Technology

Daegu Gyeongbuk Institute of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In many practical situations, a desirable user interface to a computer system should have a model of where a person is looking at and what user is paying attention to. This is particularly important if a system is providing multi modal communication cues, speech, gesture and the system must identify, whether the cues are aimed at it, or at someone else in the room. In this paper, we describes a system that identifies user focus of attention by visually determining where a person is looking. Our system consists of three steps. First, the head region was estimated and tracked from color image and depth map. Second, the position and orientation of head was estimated using random forests classifier. Due to this classifier, system can be operated in real time and deal with the large set of training data. Finally, calculate the position of user's gaze on the display device.

Original language	English
Title of host publication	Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014
Editors	David Al-Dabass, Gregorio Romero, Emilio Corchado, Athanasios Pantelous, Ismail Saad, Alessandra Orsoni
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	166-171
Number of pages	6
ISBN (Electronic)	9781479975990
DOIs	https://doi.org/10.1109/AIMS.2014.48
State	Published - 5 May 2014
Event	2nd IEEE International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014 - Madrid, Spain Duration: 18 Nov 2014 → 20 Nov 2014

Publication series

Name	Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014

Conference

Conference	2nd IEEE International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014
Country/Territory	Spain
City	Madrid
Period	18/11/14 → 20/11/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

face detection
face tracking
gaze tracking
head pose estimation
random forests

Access to Document

10.1109/AIMS.2014.48

Cite this

Kim, H., Sohn, M. K., Kim, D. J., & Ryu, N. (2014). User's Gaze Tracking System and Its Application Using Head Pose Estimation. In D. Al-Dabass, G. Romero, E. Corchado, A. Pantelous, I. Saad, & A. Orsoni (Eds.), Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014 (pp. 166-171). Article 7102454 (Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AIMS.2014.48

Kim, Hyunduk ; Sohn, Myoung Kyu ; Kim, Dong Ju et al. / User's Gaze Tracking System and Its Application Using Head Pose Estimation. Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014. editor / David Al-Dabass ; Gregorio Romero ; Emilio Corchado ; Athanasios Pantelous ; Ismail Saad ; Alessandra Orsoni. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 166-171 (Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014).

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title = "User's Gaze Tracking System and Its Application Using Head Pose Estimation",

abstract = "In many practical situations, a desirable user interface to a computer system should have a model of where a person is looking at and what user is paying attention to. This is particularly important if a system is providing multi modal communication cues, speech, gesture and the system must identify, whether the cues are aimed at it, or at someone else in the room. In this paper, we describes a system that identifies user focus of attention by visually determining where a person is looking. Our system consists of three steps. First, the head region was estimated and tracked from color image and depth map. Second, the position and orientation of head was estimated using random forests classifier. Due to this classifier, system can be operated in real time and deal with the large set of training data. Finally, calculate the position of user's gaze on the display device.",

keywords = "face detection, face tracking, gaze tracking, head pose estimation, random forests",

author = "Hyunduk Kim and Sohn, {Myoung Kyu} and Kim, {Dong Ju} and Nuri Ryu",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2nd IEEE International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014 ; Conference date: 18-11-2014 Through 20-11-2014",

year = "2014",

month = may,

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doi = "10.1109/AIMS.2014.48",

language = "English",

series = "Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014",

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editor = "David Al-Dabass and Gregorio Romero and Emilio Corchado and Athanasios Pantelous and Ismail Saad and Alessandra Orsoni",

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Kim, H, Sohn, MK, Kim, DJ & Ryu, N 2014, User's Gaze Tracking System and Its Application Using Head Pose Estimation. in D Al-Dabass, G Romero, E Corchado, A Pantelous, I Saad & A Orsoni (eds), Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014., 7102454, Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014, Institute of Electrical and Electronics Engineers Inc., pp. 166-171, 2nd IEEE International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014, Madrid, Spain, 18/11/14. https://doi.org/10.1109/AIMS.2014.48

User's Gaze Tracking System and Its Application Using Head Pose Estimation. / Kim, Hyunduk; Sohn, Myoung Kyu; Kim, Dong Ju et al.
Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014. ed. / David Al-Dabass; Gregorio Romero; Emilio Corchado; Athanasios Pantelous; Ismail Saad; Alessandra Orsoni. Institute of Electrical and Electronics Engineers Inc., 2014. p. 166-171 7102454 (Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - User's Gaze Tracking System and Its Application Using Head Pose Estimation

AU - Kim, Hyunduk

AU - Sohn, Myoung Kyu

AU - Kim, Dong Ju

AU - Ryu, Nuri

PY - 2014/5/5

Y1 - 2014/5/5

N2 - In many practical situations, a desirable user interface to a computer system should have a model of where a person is looking at and what user is paying attention to. This is particularly important if a system is providing multi modal communication cues, speech, gesture and the system must identify, whether the cues are aimed at it, or at someone else in the room. In this paper, we describes a system that identifies user focus of attention by visually determining where a person is looking. Our system consists of three steps. First, the head region was estimated and tracked from color image and depth map. Second, the position and orientation of head was estimated using random forests classifier. Due to this classifier, system can be operated in real time and deal with the large set of training data. Finally, calculate the position of user's gaze on the display device.

AB - In many practical situations, a desirable user interface to a computer system should have a model of where a person is looking at and what user is paying attention to. This is particularly important if a system is providing multi modal communication cues, speech, gesture and the system must identify, whether the cues are aimed at it, or at someone else in the room. In this paper, we describes a system that identifies user focus of attention by visually determining where a person is looking. Our system consists of three steps. First, the head region was estimated and tracked from color image and depth map. Second, the position and orientation of head was estimated using random forests classifier. Due to this classifier, system can be operated in real time and deal with the large set of training data. Finally, calculate the position of user's gaze on the display device.

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BT - Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014

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A2 - Pantelous, Athanasios

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PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 18 November 2014 through 20 November 2014

ER -

Kim H, Sohn MK, Kim DJ, Ryu N. User's Gaze Tracking System and Its Application Using Head Pose Estimation. In Al-Dabass D, Romero G, Corchado E, Pantelous A, Saad I, Orsoni A, editors, Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 166-171. 7102454. (Proceedings - 2nd International Conference on Artificial Intelligence, Modelling, and Simulation, AIMS 2014). doi: 10.1109/AIMS.2014.48

User's Gaze Tracking System and Its Application Using Head Pose Estimation

Abstract

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Keywords

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