Efficient Emotional Relaxation Framework with Anisotropic Features Based Dijkstra Algorithm (이방성 특징 기반 다익스트라 알고리즘을 이용한 효율적인 감성 완화 프레임워크)

Jong-Hyun Kim (김종현)

doi:10.9708/jksci.2020.25.04.079

Efficient Emotional Relaxation Framework with Anisotropic Features Based Dijkstra Algorithm

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2020, 25(4), pp.79-86
DOI : 10.9708/jksci.2020.25.04.079
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : March 23, 2020
Accepted : April 21, 2020
Published : April 30, 2020

Jong-Hyun Kim ¹

¹강남대학교

Accredited

ABSTRACT

In this paper, we propose an efficient emotional relaxation framework using Dijkstra algorithm based on anisotropic features. Emotional relaxation is as important as emotional analysis. This is a framework that can automatically alleviate the person's depression or loneliness. This is very important for HCI (Human-Computer Interaction). In this paper, 1) Emotion value changing from facial expression is calculated using Microsoft 's Emotion API, 2) Using these differences in emotion values, we recognize abnormal feelings such as depression or loneliness. 3) Finally, emotional mesh based matching process considering the emotional histogram and anisotropic characteristics is proposed, which suggests emotional relaxation to the user. In this paper, we propose a system which can recognize the change of emotion easily by using face image and train personal emotion by emotion relaxation.

KEYWORDS

Emotional relaxation, anisotropic features, Dijkstra algorithm, Human-computer interaction

Citation status

* References for papers published after 2023 are currently being built.

[journal] Neha Jain / 2018 / Hybrid deep neural networks for face emotion recognition / Pattern Recognition Letters / Elsevier BV 115 : 101~106

[confproc] Liu / 2014 / Facial expression recognition via a boosted deep belief network / Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition : 1805~1812

[confproc] Parkhi, Omkar M. / 2015 / Deep face recognition / The British Machine Vision Conference 1(3) : 6~

[confproc] Chen, Yang / 2018 / Cartoongan:Generative adversarial networks for photo cartoonization / Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition : 9465~9474

[confproc] Geng, Jiahao / 2018 / Warp-guided GANs for single-photo facial animation / SIGGRAPH Asia : 231~

[journal] Paul Ekman / 2008 / An argument for basic emotions / Cognition and Emotion / Informa UK Limited 6(3-4) : 169~200

[confproc] Vogt, Thurid / 2006 / Improving Automatic Emotion Recognition from Speech via Gender Differentiaion / International Conference on Language Resources and Evaluation : 1123~1126

[confproc] Nakasone, Arturo / 2005 / Emotion recognition from electromyography and skin conductance / International Workshop on Biosignal Interpretation : 219~222

[journal] NDimberg, U. / 1988 / Facial electromyography and the experience of emotion / Journal of Psychophysiology

[journal] Mase, K. / 1991 / Recognition of facial expression from optical flow / IEICE Transactions on Information and Systems 74(10) : 3474~3483

[confproc] Cohen, I. / 2002 / Facial expression recognition from video sequences / International Conference on Multimedia and Expo 2 : 121~124

[journal] 염홍기 / 2008 / Emotion Recognition and Expression System of User using Multi-Modal Sensor Fusion Algorithm / 한국지능시스템학회 논문지 / 한국지능시스템학회 18(1) : 20~26

[journal] Peter J B Hancock / 2009 / The principal components of natural images / Network: Computation in Neural Systems / Informa UK Limited 3(1) : 61~70

[journal] Juwei Lu / 2003 / Face recognition using LDA-based algorithms / IEEE Transactions on Neural Networks / Institute of Electrical and Electronics Engineers (IEEE) 14(1) : 195~200

[journal] Pierre Comon / 1994 / Independent component analysis, A new concept? / Signal Processing / Elsevier BV 36(3) : 287~314

[book] Del Sole, Alessandro / 2018 / Microsoft Computer Vision APIs Distilled / Apress : 1~4

[journal] E. Reinhard / 2001 / Color transfer between images / IEEE Computer Graphics and Applications / Institute of Electrical and Electronics Engineers (IEEE) 21(4) : 34~41

[confproc] Youngha Chang / 2003 / Color transformation based on Basic Color Categories of a Painting / Proceedings of Computer Graphics International : 176~181

[book] B. Berlin / 1969 / Basic Color Terms: Their Universality and Evolution / University of California Press

[journal] Donald H. House / 2003 / Image Recoloring Induced by Palette Color Associations / Journal of WSCG 11(1) : 189~196

[confproc] Jiaya Jia / 2005 / Local Color Transfer via Probabilistic Segmentation by Expectation-Maximization / IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1 : 747~754

[confproc] V. Konushin / 2006 / Interactive Image Colorization and Recoloring Based on Coupled Map Lattices / Graphicon'2006Conference Proceedings : 231~234

[journal] Chuan-Kai Yang / 2008 / Automatic Mood-Transferring between Color Images / IEEE Computer Graphics and Applications / Institute of Electrical and Electronics Engineers (IEEE) 28(2) : 52~61

[other] Cho J / 2019 / Deep neural networks for emotion recognition combining audio and transcripts / arXiv preprint arXiv:1911.00432.

[journal] J.A. Domínguez-Jiménez / 2020 / A machine learning model for emotion recognition from physiological signals / Biomedical Signal Processing and Control / Elsevier BV 55 : 101646~

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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Efficient Emotional Relaxation Framework with Anisotropic Features Based Dijkstra Algorithm

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* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Efficient Emotional Relaxation Framework with Anisotropic Features Based Dijkstra Algorithm

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KEYWORDS

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* References for papers published after 2023 are currently being built.