short-paper

Real-Time Emotion Detection via E-See

Authors:

Fei Ma,

Shiguang NiAuthors Info & Claims

SenSys '18: Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems

Pages 420 - 421

https://doi.org/10.1145/3274783.3275213

Published: 04 November 2018 Publication History

Get Access

Abstract

Real-time emotion detection has being attracted to human attention recently. Recognizing the inner emotion not only assists people to communicate and understand with each other, but also prevents the occurrence of the serious diseases (e.g., autism) and the emergency (i.e., child abuse, sexual invasion). Existing works usually adopt the professional and cumbersome devices to learn the emotions, and therefore limited in the daily usage. In this work, we design a pervasive and wearable device E-See that enables to recognize the emotion in real time. The prototype of the device is deployed in a microcomputer currently, and it can be resized as a small button worn on the collar or extend as a platform to detect the real-time emotion.

References

[1]

Theodoros Giannakopoulos. 2015. pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis. PloS one 10, 12 (2015).

Google Scholar

[2]

Weixi Gu. 2017. PhD Forum Abstract: Non-intrusive Blood Glucose Monitor by Multi-task Deep Learning. In Information Processing in Sensor Networks (IPSN), 2017 16th ACM/IEEE International Conference on. IEEE, 249--250.

Digital Library

Google Scholar

[3]

Weixi Gu, Longfei Shangguan, Zheng Yang, and Yunhao Liu. 2016. Sleep hunter: Towards fine grained sleep stage tracking with smartphones. IEEE Transactions on Mobile Computing 15, 6 (2016), 1514--1527.

Crossref

Google Scholar

[4]

Weixi Gu, Zheng Yang, Longfei Shangguan, Wei Sun, Kun Jin, and Yunhao Liu. 2014. Intelligent sleep stage mining service with smartphones. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 649--660.

Digital Library

Google Scholar

[5]

Weixi Gu, Kai Zhang, Zimu Zhou, Ming Jin, Yuxun Zhou, Xi Liu, Costas J Spanos, Zuo-Jun Max Shen, Wei-Hua Lin, and Lin Zhang. 2017. Measuring fine-grained metro interchange time via smartphones. Transportation research part C: emerging technologies 81 (2017), 153--171.

Google Scholar

[6]

Weixi Gu, Yuxun Zhou, Zimu Zhou, Xi Liu, Han Zou, Pei Zhang, Costas J Spanos, and Lin Zhang. 2017. Sugarmate: Non-intrusive blood glucose monitoring with smartphones. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 54.

Digital Library

Google Scholar

[7]

Weixi Gu, Zimu Zhou, Yuxun Zhou, Miao He, Han Zou, and Lin Zhang. 2017. Predicting Blood Glucose Dynamics with Multi-time-series Deep Learning. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. ACM, 55.

Digital Library

Google Scholar

[8]

Weixi Gu, Zimu Zhou, Yuxun Zhou, Han Zou, Yunxin Liu, Costas J Spanos, and Lin Zhang. 2017. BikeMate: Bike Riding Behavior Monitoring with Smartphones. In Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2017. ACM.

Digital Library

Google Scholar

[9]

Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. 1097--1105.

Digital Library

Google Scholar

[10]

Robert LiKamWa, Yunxin Liu, Nicholas D Lane, and Lin Zhong. 2013. Moodscope: Building a mood sensor from smartphone usage patterns. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. ACM, 389--402.

Digital Library

Google Scholar

[11]

Fei Tao, Gang Liu, and Qingen Zhao. 2018. An Ensemble Framework of Voice-Based Emotion Recognition System for Films and TV Programs. arXiv preprint arXiv:1803.01122 (2018).

Google Scholar

Cited By

View all

Ma FLi YNi SHuang SZhang L(2022)Data Augmentation for Audio-Visual Emotion Recognition with an Efficient Multimodal Conditional GANApplied Sciences10.3390/app1201052712:1(527)Online publication date: 5-Jan-2022
https://doi.org/10.3390/app12010527
He MGu WZhou YKong YZhang LHarle RFarrahi KLane N(2019)Causal feature selection for physical sensing dataAdjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers10.1145/3341162.3349333(565-570)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3341162.3349333

Index Terms

Real-Time Emotion Detection via E-See
1. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Real-Time Emotion Detection System’s Impact on Pivotal Response Training Protocol
Artificial Intelligence for Neuroscience and Emotional Systems
Abstract
In recent years, there has been a growing emphasis on Autism Spectrum Disorder (ASD), marked by evolving classifications and increasing global prevalence. Early intervention is underscored as crucial for effective management of ASD, given that ...
Real-Time Movie-Induced Discrete Emotion Recognition from EEG Signals
Recognition of a human's continuous emotional states in real time plays an important role in machine emotional intelligence and human-machine interaction. Existing real-time emotion recognition systems use stimuli with low ecological validity (e.g.,...
Improved Multimodal Emotion Recognition for Better Game-Based Learning
GALA 2014: Revised Selected Papers from the Third International Conference on Games and Learning Alliance - Volume 9221

This paper introduces the integration of the face emotion recognition part and the voice emotion recognition part of our FILTWAM framework that uses webcams and microphones. This framework enables real-time multimodal emotion recognition of learners ...

Comments

Information & Contributors

Information

Published In

SenSys '18: Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems

November 2018

449 pages

ISBN:9781450359528

DOI:10.1145/3274783

Editors:
Gowri Sankar Ramachandran
University of Southern California, Los Angeles
,
Bhaskar Krishnamachari
University of Southern California, Los Angeles

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 November 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tag

Real-Time Emotion Recognition

Qualifiers

Short-paper
Research
Refereed limited

Conference

SenSys '18

Sponsor:

SenSys '18: The 16th ACM Conference on Embedded Networked Sensor Systems

November 4 - 7, 2018

Shenzhen, China

Acceptance Rates

Overall Acceptance Rate 198 of 990 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
317
Total Downloads

Downloads (Last 12 months)19
Downloads (Last 6 weeks)2

Reflects downloads up to 24 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Ma FLi YNi SHuang SZhang L(2022)Data Augmentation for Audio-Visual Emotion Recognition with an Efficient Multimodal Conditional GANApplied Sciences10.3390/app1201052712:1(527)Online publication date: 5-Jan-2022
https://doi.org/10.3390/app12010527
He MGu WZhou YKong YZhang LHarle RFarrahi KLane N(2019)Causal feature selection for physical sensing dataAdjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers10.1145/3341162.3349333(565-570)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3341162.3349333

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Real-Time Emotion Detection System’s Impact on Pivotal Response Training Protocol

Real-Time Movie-Induced Discrete Emotion Recognition from EEG Signals

Improved Multimodal Emotion Recognition for Better Game-Based Learning

Comments

Information

Published In

Sponsors

Publisher

Publication History

Permissions

Check for updates

Author Tag

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations