Web-based Visualisation of Head Pose and Facial Expressions Changes: Monitoring Human Activity Using Depth Data.

Grigorios Kalliatakis, Nikolaos Vidakis, Georgios Triantafyllidis

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generating
comprehensible visual representations from different sets of data, we introduce a system capable of monitoring human activity through head pose and facial expression changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor). An approach build on discriminative random regression forests was selected in order to rapidly and accurately estimate head pose changes in unconstrained environment. In
order to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data exchange format (JavaScript Object Notation-JSON) is employed, in order to manipulate the data extracted from the two aforementioned settings. Such mechanism can yield a platform for objective and effortless assessment of human activity within the context of serious gaming and human-computer interaction.
Original languageEnglish
Title of host publicationComputer Science and Electronic Engineering (CEEC), 2016 8th
PublisherIEEE
Publication dateSep 2016
ISBN (Print)978-1-5090-1275-6
ISBN (Electronic)978-1-5090-2050-8
DOIs
Publication statusPublished - Sep 2016
Event8th Computer Science & Electronic Engineering Conference - University of Essex in Colchester, Essex, United Kingdom
Duration: 28 Sep 201630 Sep 2016
http://ceec.uk/

Conference

Conference8th Computer Science & Electronic Engineering Conference
LocationUniversity of Essex in Colchester
CountryUnited Kingdom
CityEssex
Period28/09/201630/09/2016
Internet address

Fingerprint

Electronic data interchange
Human computer interaction
Visualization
Monitoring
Sensors

Cite this

Kalliatakis, Grigorios ; Vidakis, Nikolaos ; Triantafyllidis, Georgios. / Web-based Visualisation of Head Pose and Facial Expressions Changes: Monitoring Human Activity Using Depth Data. Computer Science and Electronic Engineering (CEEC), 2016 8th. IEEE, 2016.
@inproceedings{e7acf90099664f9b931cd131c6c0aac1,
title = "Web-based Visualisation of Head Pose and Facial Expressions Changes:: Monitoring Human Activity Using Depth Data.",
abstract = "Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generatingcomprehensible visual representations from different sets of data, we introduce a system capable of monitoring human activity through head pose and facial expression changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor). An approach build on discriminative random regression forests was selected in order to rapidly and accurately estimate head pose changes in unconstrained environment. Inorder to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data exchange format (JavaScript Object Notation-JSON) is employed, in order to manipulate the data extracted from the two aforementioned settings. Such mechanism can yield a platform for objective and effortless assessment of human activity within the context of serious gaming and human-computer interaction.",
author = "Grigorios Kalliatakis and Nikolaos Vidakis and Georgios Triantafyllidis",
year = "2016",
month = "9",
doi = "10.1109/CEEC.2016.7835887",
language = "English",
isbn = "978-1-5090-1275-6",
booktitle = "Computer Science and Electronic Engineering (CEEC), 2016 8th",
publisher = "IEEE",
address = "United States",

}

Kalliatakis, G, Vidakis, N & Triantafyllidis, G 2016, Web-based Visualisation of Head Pose and Facial Expressions Changes: Monitoring Human Activity Using Depth Data. in Computer Science and Electronic Engineering (CEEC), 2016 8th. IEEE, 8th Computer Science & Electronic Engineering Conference, Essex, United Kingdom, 28/09/2016. https://doi.org/10.1109/CEEC.2016.7835887

Web-based Visualisation of Head Pose and Facial Expressions Changes: Monitoring Human Activity Using Depth Data. / Kalliatakis, Grigorios; Vidakis, Nikolaos; Triantafyllidis, Georgios.

Computer Science and Electronic Engineering (CEEC), 2016 8th. IEEE, 2016.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

T1 - Web-based Visualisation of Head Pose and Facial Expressions Changes:

T2 - Monitoring Human Activity Using Depth Data.

AU - Kalliatakis, Grigorios

AU - Vidakis, Nikolaos

AU - Triantafyllidis, Georgios

PY - 2016/9

Y1 - 2016/9

N2 - Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generatingcomprehensible visual representations from different sets of data, we introduce a system capable of monitoring human activity through head pose and facial expression changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor). An approach build on discriminative random regression forests was selected in order to rapidly and accurately estimate head pose changes in unconstrained environment. Inorder to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data exchange format (JavaScript Object Notation-JSON) is employed, in order to manipulate the data extracted from the two aforementioned settings. Such mechanism can yield a platform for objective and effortless assessment of human activity within the context of serious gaming and human-computer interaction.

AB - Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generatingcomprehensible visual representations from different sets of data, we introduce a system capable of monitoring human activity through head pose and facial expression changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor). An approach build on discriminative random regression forests was selected in order to rapidly and accurately estimate head pose changes in unconstrained environment. Inorder to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data exchange format (JavaScript Object Notation-JSON) is employed, in order to manipulate the data extracted from the two aforementioned settings. Such mechanism can yield a platform for objective and effortless assessment of human activity within the context of serious gaming and human-computer interaction.

U2 - 10.1109/CEEC.2016.7835887

DO - 10.1109/CEEC.2016.7835887

M3 - Article in proceeding

SN - 978-1-5090-1275-6

BT - Computer Science and Electronic Engineering (CEEC), 2016 8th

PB - IEEE

ER -