Emotion recognition using image processing

Undergraduate thesis submitted to the Department of Computer Science, Ashesi University, in partial fulfillment of Bachelor of Science degree in Computer Science, May 2020Emotion recognition is an active field of research that has seen a lot of interest over the past decade. Historically, people’s emotions were analysed and determined through human observation and psychological counselling and later evolved to electrophysiological and largely intrusive methods such as Electroencephalography (EEG) because of how complex of a task it is and how extensive its application could be. Currently, with the entrance of machine learning and computer vision-related technologies, computers and robots can now be trained to learn and predict the emotions of human beings either in real-time or with their static facial images. In this research, emotion recognition is explored with respect to its three widely recognised stages: face detection, feature extraction and emotion recognition. At each of these stages, different image processing methods and learning techniques are explored and tested. A Convolutional Neural Network was trained and tested and recorded an accuracy of 50.7%. A Support Vector Machine was also trained and tested and recorded an accuracy of 81.5%. Both classifiers were trained on 7 emotion categories. The results show that it is possible for computers to predict the emotions of humans using image processing techniques and deep learning models. ; deep learning; ; image processing;Ashesi Universit

Online Privacy Control Via Anonymity And Pseudonym: Cross-Cultural Implications

Privacy’s exact nature needs to re?ect the contemporary view of a society. A growing number of online users demand the protection of their personal privacy via anonymity and pseudonym. The e?cacy of these two privacy controls in di?erent online environments is unknown. This study applies social psychology theories to explore the relationship between these personal sentiments—authoritative personality, empathy, fear of negative evaluation, self-esteem, and motives of online privacy rights. We conducted a quasi-experiment by manipulating four online environments (personal e-mail exchange, members-only newsgroup, public newsgroup, and online chat room), and three user identi?cation modes (real name, anonymity and pseudonym). More than 600 subjects from the USA and Taiwan participated in the experimental study. The results of path analysis con?rm the e?ects of some personal sentiments on the motives of online privacy rights. The study concludes with theoretical and practical implications for the roles of privacy in the online society

Essays in Leadership Communication

This work centers around leadership communication: how our (dis)information-rich and uncertain global environment has posed challenges to and offered opportunities for this key leadership behavior, and how leaders engage in difficult communications with their stakeholders. I focus on leader-stakeholder two-way dynamics to investigate leader communication in critical moments when they deliver undesirable information to their stakeholders and respond to tough questions from their stakeholders. Essay I reviews research on leader communication and discusses those challenges and opportunities. Essay II uses 107 million Twitter posts to examine stakeholder responses to political leaders’ COVID-19 communications and illustrates the evolving leader-stakeholder relationship throughout different phases of the global pandemic. Essay III explores organizational leaders’ response strategies when facing difficult questions from stakeholders in high-stakes corporate environments. In conclusion, I aim to highlight leaders’ indispensable responsibilities to communicate effectively, benevolently, and responsibly, enhancing the field’s current understanding of crisis leadership, followership, and strategic leadership

Pathway to Future Symbiotic Creativity

This report presents a comprehensive view of our vision on the development path of the human-machine symbiotic art creation. We propose a classification of the creative system with a hierarchy of 5 classes, showing the pathway of creativity evolving from a mimic-human artist (Turing Artists) to a Machine artist in its own right. We begin with an overview of the limitations of the Turing Artists then focus on the top two-level systems, Machine Artists, emphasizing machine-human communication in art creation. In art creation, it is necessary for machines to understand humans' mental states, including desires, appreciation, and emotions, humans also need to understand machines' creative capabilities and limitations. The rapid development of immersive environment and further evolution into the new concept of metaverse enable symbiotic art creation through unprecedented flexibility of bi-directional communication between artists and art manifestation environments. By examining the latest sensor and XR technologies, we illustrate the novel way for art data collection to constitute the base of a new form of human-machine bidirectional communication and understanding in art creation. Based on such communication and understanding mechanisms, we propose a novel framework for building future Machine artists, which comes with the philosophy that a human-compatible AI system should be based on the "human-in-the-loop" principle rather than the traditional "end-to-end" dogma. By proposing a new form of inverse reinforcement learning model, we outline the platform design of machine artists, demonstrate its functions and showcase some examples of technologies we have developed. We also provide a systematic exposition of the ecosystem for AI-based symbiotic art form and community with an economic model built on NFT technology. Ethical issues for the development of machine artists are also discussed

Pandemic Emotions: The Good, The Bad, and The Unconscious —Implications for Public Health, Financial Economics, Law, and Leadership

Pandemics lead to emotions that can be good, bad, and unconscious. This Article offers an interdisciplinary analysis of how emotions during pandemics affect people’s responses to pandemics, public health, financial economics, law, and leadership. Pandemics are heart-breaking health crises. Crises produce emotions that impact decision-making. This Article analyzes how fear and anger over COVID-19 fueled anti-Asian and anti-Asian American hatred and racism. COVID-19 caused massive tragic economic, emotional, mental, physical, and psychological suffering. These difficulties are interconnected and lead to vicious cycles. Fear distorts people’s decision readiness, deliberation, information acquisition, risk perception, and thinking. Distortions affect people’s financial, health, and political decisions, causing additional fears. Emotions have direct health impacts and indirect behavioral impacts, which in turn have their own health impacts. People differ vastly in whether, how much, and when they experience anxiety, complacency, and panic during pandemics. A common path is to feel some anxiety initially, then panic, and finally become complacent. This Article advocates these responses to pandemics: (1) paying people directly monthly pandemic financial assistance, (2) encouraging people to practice mindfulness, (3) gently enforcing Non-Pharmaceutical Interventions, (4) fostering accurate information acquisition about pandemics, and (5) applying psychological game theory to better understand emotions that depend on beliefs about leadership

Analysis and automation of remedies for community hardships of non-native community

Abstract. Equality among all human beings, as a world community surpassing all the barriers such as religion, language, ethnicity, geographical location, and nationality is an important aspect all over the world. The equality for non-native communities of the country is a more important aspect of human equality. The hardships faced by the non-native community of society due to lack of equality cause irreversible damage to humankind and society. Lately, with the development of many technologies and new implementations, the fact that these technologies can assist in solving social problems came into discussion. Considering the hardships faced by non-native communities in terms of a social problem we explore how technology can assist in solving social matters. Thereby we explore a novel vision for the part that technology can contribute in solving civic matters encompassing frameworks from public engagement, crowdsourcing, and design thinking. In this thesis, we do a study on background work on how we can solve civic matters by assisting public participation frameworks, crowdsourcing frameworks, and design thinking frameworks. For this purpose, we presented three hardship stories that the non-native community of Finnish university faces which have been collected through a previous study, to collect ideas, and thoughts on how to mitigate the situation. We employed three questionnaires designed based on three conditions the conditions were First one is the baseline where the answers to the questionnaires will not be analyzed anywhere, and the second questionnaire condition is that the ideas will be used in social media and the third is that the ideas will be subjected to a quality analysis by crowd workers. To this end, we have collected ideas from 40 participants for each questionnaire with the aid of a prolific crowd-sourcing platform. Each of the questionnaires included a Questionnaire of Cognitive and Affective Empathy (QCAE) questionnaire section to measure empathy. Further, we Analyse the data that we have collected, through a QCAE analysis, word count, and answer length analysis, analyzing the co-relations between them, doing thematic coding, and doing a tone analysis. Moreover, we implemented an automated pipeline to do tone analysis starting from fetching answers from google forms to output the tone analysis results. Ultimately, the thesis contributes to Collecting ideas on how to mitigate the hardship experiences faced by non-native communities in a Finnish university. Further enhances the awareness of the hardships faced by the non-native community of a society. And through the analysis of the results we identified different co-relations between different factors like word count and Empathy. Analyze the tone of the participants in civic issues. Finally discussed the part that technology can contribute in solving civic matters encompassing frameworks from public engagement, crowdsourcing and design thinking

Strategies for ESL Students in Community Colleges to Develop Their Public Speaking Skills

The purpose of this project was to identify strategies for ESL students in community colleges to develop their public speaking skills. Effective oral communication skills are commonly needed by employees in the workplace at all different levels. The project focused on three key areas: 1) ways to reduce the fear and anxiety associated with public speaking; 2) the role of small groups in planning and presenting oral presentations; and 3) the use of feedback and self-help strategies to improve public speaking skills. The project presented a handbook of strategies in each of these areas for students to use as a resource in developing these skills. With increased self-confidence and strengthened public speaking skills, community college ESL students will be better prepared to succeed in their further education and as employees in the workforce

Adaptive Multimodal Emotion Detection Architecture for Social Robots

Emotion recognition is a strategy for social robots used to implement better Human-Robot Interaction and model their social behaviour. Since human emotions can be expressed in different ways (e.g., face, gesture, voice), multimodal approaches are useful to support the recognition process. However, although there exist studies dealing with multimodal emotion recognition for social robots, they still present limitations in the fusion process, dropping their performance if one or more modalities are not present or if modalities have different qualities. This is a common situation in social robotics, due to the high variety of the sensory capacities of robots; hence, more flexible multimodal models are needed. In this context, we propose an adaptive and flexible emotion recognition architecture able to work with multiple sources and modalities of information and manage different levels of data quality and missing data, to lead robots to better understand the mood of people in a given environment and accordingly adapt their behaviour. Each modality is analyzed independently to then aggregate the partial results with a previous proposed fusion method, called EmbraceNet+, which is adapted and integrated to our proposed framework. We also present an extensive review of state-of-the-art studies dealing with fusion methods for multimodal emotion recognition approaches. We evaluate the performance of our proposed architecture by performing different tests in which several modalities are combined to classify emotions using four categories (i.e., happiness, neutral, sadness, and anger). Results reveal that our approach is able to adapt to the quality and presence of modalities. Furthermore, results obtained are validated and compared with other similar proposals, obtaining competitive performance with state-of-the-art models

Basic Communication Course Annual Vol. 8

(207 Pages, 7.696 MB