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  • Open Access

    ARTICLE

    Negative Emotions Sensitive Humanoid Robot with Attention-Enhanced Facial Expression Recognition Network

    Rongrong Ni1, Xiaofeng Liu1,*, Yizhou Chen1, Xu Zhou1, Huili Cai1, Loo Chu Kiong2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 149-164, 2022, DOI:10.32604/iasc.2022.026813 - 15 April 2022

    Abstract Lonely older adults and persons restricted in movements are apt to cause negative emotions, which is harmful to their mental health. A humanoid robot with audiovisual interactions is presented, which can correspondingly output positive facial expressions to relieve human's negative facial expressions. The negative emotions are identified through an attention-enhanced facial expression recognition (FER) network. The network is firstly trained on MMEW macro-and micro-expression databases to discover expression-related features. Then, macro-expression recognition tasks are performed by fine-tuning the trained models on several benchmarking FER databases, including CK+ and Oulu-CASIA. A transformer network is introduced to More >

  • Open Access

    ARTICLE

    Game Outlier Behavior Detection System Based on Dynamic Time Warp Algorithm

    Shinjin Kang1, Soo Kyun Kim2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 219-237, 2022, DOI:10.32604/cmes.2022.018413 - 24 January 2022

    Abstract This paper proposes a methodology for using multi-modal data in gameplay to detect outlier behavior. The proposed methodology collects, synchronizes, and quantifies time-series data from webcams, mouses, and keyboards. Facial expressions are varied on a one-dimensional pleasure axis, and changes in expression in the mouth and eye areas are detected separately. Furthermore, the keyboard and mouse input frequencies are tracked to determine the interaction intensity of users. Then, we apply a dynamic time warp algorithm to detect outlier behavior. The detected outlier behavior graph patterns were the play patterns that the game designer did not More >

  • Open Access

    ARTICLE

    Automated Facial Expression Recognition and Age Estimation Using Deep Learning

    Syeda Amna Rizwan1, Yazeed Yasin Ghadi2, Ahmad Jalal1, Kibum Kim3,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5235-5252, 2022, DOI:10.32604/cmc.2022.023328 - 14 January 2022

    Abstract With the advancement of computer vision techniques in surveillance systems, the need for more proficient, intelligent, and sustainable facial expressions and age recognition is necessary. The main purpose of this study is to develop accurate facial expressions and an age recognition system that is capable of error-free recognition of human expression and age in both indoor and outdoor environments. The proposed system first takes an input image pre-process it and then detects faces in the entire image. After that landmarks localization helps in the formation of synthetic face mask prediction. A novel set of features More >

  • Open Access

    ARTICLE

    Face Recognition System Using Deep Belief Network and Particle Swarm Optimization

    K. Babu1,*, C. Kumar2, C. Kannaiyaraju3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756 - 05 January 2022

    Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component… More >

  • Open Access

    ARTICLE

    Empathic Responses of Behavioral-Synchronization in Human-Agent Interaction

    Sung Park1,*, Seongeon Park2, Mincheol Whang2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3761-3784, 2022, DOI:10.32604/cmc.2022.023738 - 07 December 2021

    Abstract Artificial entities, such as virtual agents, have become more pervasive. Their long-term presence among humans requires the virtual agent's ability to express appropriate emotions to elicit the necessary empathy from the users. Affective empathy involves behavioral mimicry, a synchronized co-movement between dyadic pairs. However, the characteristics of such synchrony between humans and virtual agents remain unclear in empathic interactions. Our study evaluates the participant's behavioral synchronization when a virtual agent exhibits an emotional expression congruent with the emotional context through facial expressions, behavioral gestures, and voice. Participants viewed an emotion-eliciting video stimulus (negative or positive)… More >

  • Open Access

    ARTICLE

    Sentiment Analysis on Social Media Using Genetic Algorithm with CNN

    Dharmendra Dangi*, Amit Bhagat, Dheeraj Kumar Dixit

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5399-5419, 2022, DOI:10.32604/cmc.2022.020431 - 11 October 2021

    Abstract There are various intense forces causing customers to use evaluated data when using social media platforms and microblogging sites. Today, customers throughout the world share their points of view on all kinds of topics through these sources. The massive volume of data created by these customers makes it impossible to analyze such data manually. Therefore, an efficient and intelligent method for evaluating social media data and their divergence needs to be developed. Today, various types of equipment and techniques are available for automatically estimating the classification of sentiments. Sentiment analysis involves determining people's emotions using… More >

  • Open Access

    ARTICLE

    Facial Expression Recognition Using Enhanced Convolution Neural Network with Attention Mechanism

    K. Prabhu1,*, S. SathishKumar2, M. Sivachitra3, S. Dineshkumar2, P. Sathiyabama4

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 415-426, 2022, DOI:10.32604/csse.2022.019749 - 08 October 2021

    Abstract Facial Expression Recognition (FER) has been an interesting area of research in places where there is human-computer interaction. Human psychology, emotions and behaviors can be analyzed in FER. Classifiers used in FER have been perfect on normal faces but have been found to be constrained in occluded faces. Recently, Deep Learning Techniques (DLT) have gained popularity in applications of real-world problems including recognition of human emotions. The human face reflects emotional states and human intentions. An expression is the most natural and powerful way of communicating non-verbally. Systems which form communications between the two are More >

  • Open Access

    ARTICLE

    Secure Rotation Invariant Face Detection System for Authentication

    Amit Verma1, Mohammed Baljon2, Shailendra Mishra2,*, Iqbaldeep Kaur1, Ritika Saini1, Sharad Saxena3, Sanjay Kumar Sharma4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1955-1974, 2022, DOI:10.32604/cmc.2022.020084 - 07 September 2021

    Abstract Biometric applications widely use the face as a component for recognition and automatic detection. Face rotation is a variable component and makes face detection a complex and challenging task with varied angles and rotation. This problem has been investigated, and a novice algorithm, namely RIFDS (Rotation Invariant Face Detection System), has been devised. The objective of the paper is to implement a robust method for face detection taken at various angle. Further to achieve better results than known algorithms for face detection. In RIFDS Polar Harmonic Transforms (PHT) technique is combined with Multi-Block Local Binary… More >

  • Open Access

    ARTICLE

    Facial Expression Recognition Based on the Fusion of Infrared and Visible Image

    Jiancheng Zou1, Jiaxin Li1,*, Juncun Wei1, Zhengzheng Li1, Xin Yang2

    Journal on Artificial Intelligence, Vol.3, No.3, pp. 123-134, 2021, DOI:10.32604/jai.2021.027069 - 25 January 2022

    Abstract Facial expression recognition is a research hot spot in the fields of computer vision and pattern recognition. However, the existing facial expression recognition models are mainly concentrated in the visible light environment. They have insufficient generalization ability and low recognition accuracy, and are vulnerable to environmental changes such as illumination and distance. In order to solve these problems, we combine the advantages of the infrared and visible images captured simultaneously by array equipment our developed with two infrared and two visible lens, so that the fused image not only has the texture information of visible… More >

  • Open Access

    ARTICLE

    Image-Based Lifelogging: User Emotion Perspective

    Junghyun Bum1, Hyunseung Choo1, Joyce Jiyoung Whang2,*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1963-1977, 2021, DOI:10.32604/cmc.2021.014931 - 05 February 2021

    Abstract Lifelog is a digital record of an individual’s daily life. It collects, records, and archives a large amount of unstructured data; therefore, techniques are required to organize and summarize those data for easy retrieval. Lifelogging has been utilized for diverse applications including healthcare, self-tracking, and entertainment, among others. With regard to the image-based lifelogging, even though most users prefer to present photos with facial expressions that allow us to infer their emotions, there have been few studies on lifelogging techniques that focus upon users’ emotions. In this paper, we develop a system that extracts users’… More >

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