Masterarbeit, 2017
32 Seiten, Note: 3.6 out 4
The main objective of this thesis is to investigate emotional recognition using real-time facial expressions depicted by emojis. It aims to develop parameters for measuring facial expressions conveyed through emoji texting and to understand real-time facial emotion recognition. The research focuses on six basic human emotions: neutral, fear, anger, happiness, sadness, and surprise.
Chapter 1: Introduction: This chapter introduces the research topic of emotional recognition using emojis in real time. It highlights the importance of emotional recognition in human communication and discusses the challenges involved in accurately identifying emotions through visual cues. The chapter establishes the objectives of the research, which include investigating real-time emotional recognition through emojis, developing parameters for measuring facial expressions using emojis, and understanding real-time facial emotion recognition. It also provides a brief overview of existing research and techniques used in facial emotion recognition, including the use of convolutional neural networks (CNNs) and the challenges associated with limited data and variations in illumination. The chapter sets the stage for the subsequent exploration of the research methodology and results.
Emotional recognition, facial expression, emojis, real-time analysis, convolutional neural networks (CNNs), human-computer interaction, communication technology, visual communication, emotion detection, affective computing.
This document provides a comprehensive preview of a research project focusing on real-time emotional recognition using emojis as indicators of facial expressions. It details the objectives, key themes, chapter summaries, and keywords of the research.
The primary objective is to investigate real-time emotional recognition through emoji-based facial expressions. This involves developing parameters for measuring these expressions and understanding the process of real-time facial emotion recognition. The research specifically focuses on six basic emotions: neutral, fear, anger, happiness, sadness, and surprise.
Key themes include the role of emojis in communication and emotional expression, the application of visual technology (specifically convolutional neural networks or CNNs) in emotion recognition, and the challenges of accurately identifying emotions through visual cues.
Chapter 1 introduces the research topic, highlighting the importance of emotional recognition in communication and the challenges involved. It outlines the research objectives, provides a brief overview of existing research and techniques (including CNNs), and discusses challenges like limited data and varying illumination. It sets the stage for the methodology and results.
Keywords include: Emotional recognition, facial expression, emojis, real-time analysis, convolutional neural networks (CNNs), human-computer interaction, communication technology, visual communication, emotion detection, and affective computing.
The research focuses on six basic human emotions: neutral, fear, anger, happiness, sadness, and surprise.
The research utilizes convolutional neural networks (CNNs) as a key technology for emotion recognition from visual data (emojis).
This preview serves as a concise summary of the research project, providing key information for understanding its scope, methodology, and findings.
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