• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.79-85
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• 2017

Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.97-101
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• 2019

Understanding and classification of the human's emotion play an important tasks in interacting with human and machine communication systems. This paper proposes a novel emotion recognition method by extracting facial keypoints, which is able to understand and classify the human emotion, using active Appearance Model and the proposed classification model of the facial features. The existing appearance model scheme takes an expression of variations, which is calculated by the proposed classification model according to the change of human facial expression. The proposed method classifies four basic emotions (normal, happy, sad and angry). To evaluate the performance of the proposed method, we assess the ratio of success with common datasets, and we achieve the best 93% accuracy, average 82.2% in facial emotion recognition. The results show that the proposed method effectively performed well over the emotion recognition, compared to the existing schemes.

• Korean Institute of Interior Design Journal
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• v.21 no.6
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• pp.46-53
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• 2012

The purpose of present study is that according to the changing tourism environment, detailed cultural environment will be utilized in the active way as systematized theme-based cultural space, and the increase of small theme-based cultural space will contribute to active participation of customers and local development with various programs. TCS was classified to theme-based cultural space contents E5(Education, Entertainment, Experience, Emotion and Economy) in focus of contents in which software is regarded more importantly than hardware, and was analyzed as contents of ten key tourism trend of the future. The present study indicate that experience centered tourism environment stood out in theme-based cultural space, and new era of cultural tourism to which storytelling in focus of emotion is applied will be coming.

• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.39-48
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• 2016

This research aims to identify innovative companies' attention to the emotion and sensibility and its application by analyzing the contents of the corporate annual reports. Annual report is a good reference data because it describes not only various current products and services' annual activities and business performance but also corporate future direction. Sensibility is interpreted and used with various words internationally: various related terms such as sensibility, sense, emotion, feeling and affection are analyzed not only by the definition but also the interrelationship among them, and included for the contents analysis. To select the innovative companies, the researcher used 'Fast company' that is the economic journal and deducted the companies list via 'The world's 50 most innovative companies' in 2009 and 2014. Listed companies' 2009 and 2014 annual reports' contents were analyzed to identify the rate of the recognition and the application of sensibility to their business. Even though the quantitative result of the content analysis indicates not a strong relationship between corporate innovativeness and 'sensibility' qualitative result identifies companies are paying more attention to the 'sense' and 'feeling' during five years. In conclusion, the innovation that company pursues strategically is shifting from differentiation and the technological leadership to satisfying user experiences and the number of companies which express and measure user feeling and emotions are increasing.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.133-141
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• 2015

Mass multimedia contents are shared through various social media servies including social network service. As social network reveals user's current situation and interest, highly satisfactory personalized recommendation can be made when such features are applied to the recommendation system. In addition, classifying the music by emotion and using analyzed information about user's recent emotion or current situation by analyzing user's social network, it will be useful upon recommending music to the user. In this paper, we propose a music recommendation method that makes an emotion model to classify the music, classifies the music according to the emotion model, and extracts user's current emotional state represented on the social network to recommend music, and evaluates the validity of our method through experiments.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.99-108
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• 2008

This paper proposes an image retrieval system which integrates metadata, contents, and emotions in textile images. First, the proposed system searches images using metadata. Among searched images, the system retrieves similar images based on color histogram, color sketch, and emotion histogram. To extract emotion features, this paper uses emotion colors which was proposed on 160 emotion words by H. Nagumo. To enhance the user's convenience, the proposed textile image retrieval system provides additional functions as like enlarging an image, viewing color histogram, viewing color sketch, and viewing repeated patterns.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.357-369
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• 2012

The purpose of this paper is to explain and identify how atmospherics of web-sites such as graphics, colour, menu and link have an effect on consumers' emotion and satisfaction, which in turn have influence on repurchase intention in internet shopping malls. A survey study was conducted to collect the data with consumers who have experience purchase or search on internet shopping malls. Analysis of structural equation modeling with AMOS 18.0 was performed to test the research hypothesis. The results of the study are as follows: Menu and link are positively associated on consumers' emotion, but graphics and colour have not influence on both consumers' emotion and satisfaction. Consumers' emotion is positively associated on both satisfaction and repurchase intention, and then satisfaction is also positively associated on repurchase intention.

• International Journal of Contents
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• v.15 no.4
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• pp.59-64
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• 2019

In recent years, emotion recognition has been an interesting and challenging topic. Compared to facial expressions and speech modality, gesture-based emotion recognition has not received much attention with only a few efforts using traditional hand-crafted methods. These approaches require major computational costs and do not offer many opportunities for improvement as most of the science community is conducting their research based on the deep learning technique. In this paper, we propose an end-to-end deep learning approach for classifying emotions based on bodily gestures. In particular, the informative keyframes are first extracted from raw videos as input for the 3D-CNN deep network. The 3D-CNN exploits the short-term spatiotemporal information of gesture features from selected keyframes, and the convolutional LSTM networks learn the long-term feature from the features results of 3D-CNN. The experimental results on the FABO dataset exceed most of the traditional methods results and achieve state-of-the-art results for the deep learning-based technique for gesture-based emotion recognition.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.613-621
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• 2016

This paper has the first aim to analyze Elsa's magic power of why and how she, as a heroine in the animation of Frozen, is in the emotion of fear and anger. This paper will explain why these two emotions are twisted compound to identify Elsa's iced emotion in the ice kingdom. And secondly, this paper attempts to connect Elsa's fear emotion in her real life is the other flip with that of anger throughout the characters' network in Frozen, which symbolically reflect the feminine pattern of real society that Walt Disney prospects for the dream society. Through the cognitive process for Elsa's ice kingdom between emotion status and social network, we can assume the pattern of social network with emotional chart and the archetype of human emotion through the cognitive-emotional storytelling on the emotion of Elsa in Frozen.

• Review of Korea Contents Association
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• v.11 no.2
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• pp.34-39
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• 2013