Facial Emotional Classifier For Natural Interaction

The recognition of emotional information is a key step toward giving computers the ability to interact more naturally and intelligently with people. We present a simple and computationally feasible method to perform automatic emotional classification of facial expressions. We propose the use of a set of characteristic facial points (that are part of the MPEG4 feature points) to extract relevant emotional information (basically five distances, presence of wrinkles in the eyebrow and mouth shape). The method defines and detects the six basic emotions (plus the neutral one) in terms of this information and has been fine-tuned with a database of more than 1500 images. The system has been integrated in a 3D engine for managing virtual characters, allowing the exploration of new forms of natural interaction

Facial expression (mood) recognition from facial images using committee neural networks

<p>Abstract</p> <p>Background</p> <p>Facial expressions are important in facilitating human communication and interactions. Also, they are used as an important tool in behavioural studies and in medical rehabilitation. Facial image based mood detection techniques may provide a fast and practical approach for non-invasive mood detection. The purpose of the present study was to develop an intelligent system for facial image based expression classification using committee neural networks.</p> <p>Methods</p> <p>Several facial parameters were extracted from a facial image and were used to train several generalized and specialized neural networks. Based on initial testing, the best performing generalized and specialized neural networks were recruited into decision making committees which formed an integrated committee neural network system. The integrated committee neural network system was then evaluated using data obtained from subjects not used in training or in initial testing.</p> <p>Results and conclusion</p> <p>The system correctly identified the correct facial expression in 255 of the 282 images (90.43% of the cases), from 62 subjects not used in training or in initial testing. Committee neural networks offer a potential tool for image based mood detection.</p

Emotion Profiling: Ingredient for Rule based Emotion Recognition Engine

Emotions are considered to be the reflection of human thinking and decision-making process which increase his/her performance by producing an intelligent outcome. Hence it is a challenging task to embed the emotional intelligence in machine as well so that it could respond appropriately. However, present human computer interfaces still don2019;t fully utilize emotion feedback to create a more natural environment because the performance of the emotion recognition is still not very robust and reliable and far from real life experience. In this paper, we present an attempt in addressing this aspect and identifying the major challenges in the process. We introduce the concept of 2018;emotion profile2019; to evaluate an individual feature as each feature irrespective of the modality has different capability for differentiating among the various subsets of emotions. To capture the discrimination across target emotions w.r.t. each feature we propose a framework for emotion recognition built around if-then rules using certainty factors to represent uncertainty and unreliability of individual features. This technique appears to be simple and effective for these kind of problems

Tackling Age-Invariant Face Recognition with Non-Linear PLDA and Pairwise SVM

Face recognition approaches, especially those based on deep learning models, are becoming increasingly attractive for missing person identification, due to their effectiveness and the relative simplicity of obtaining information available for comparison. However, these methods still suffer from large accuracy drops when they have to tackle cross-age recognition, which is the most common condition to face in this specific task. To address these challenges, in this paper we investigate the contribution of different generative and discriminative models that extend the Probabilistic Linear Discriminant Analysis (PLDA) approach. These models aim at disentangling identity from other facial variations (including those due to age effects). As such, they can improve the age invariance characteristics of state-of-the-art deep facial embeddings. In this work, we experiment with a standard PLDA, a non-linear version of PLDA, the Pairwise Support Vector Machine (PSVM), and introduce a nonlinear version of PSVM (NL--PSVM) as a novelty. We thoroughly analyze the proposed models' performance when addressing cross-age recognition in a large and challenging experimental dataset containing around 2.5 million images of 790,000 individuals. Results on this testbed confirm the challenges in age invariant face recognition, showing significant differences in the effects of aging across embedding models, genders, age ranges, and age gaps. Our experiments show as well the effectiveness of both PLDA and its proposed extensions in reducing the age sensitivity of the facial features, especially when there are significant age differences (more than ten years) between the compared images or when age-related facial changes are more pronounced, such as during the transition from childhood to adolescence or from adolescence to adulthood. Further experiments on three standard cross-age benchmarks (MORPH2, CACD-VS and FG-NET) confirm the proposed models' effectiveness

The Visual Worlds of Social Network Sites

The central form of communication on social network sites (sns) is the communication with and through images. Accordingly, the present volume highlights images and image-based communication on sns, such as Facebook, and on nightlife platforms, such as Tilllate. First, the authors analyze the two central image categories in depth - profile images and photo albums. What follows is the portrayal of dramaturgical and staging strategies of the (semi) professional photography on the nightlife platforms, which leads to an evaluation of the importance of the international glamour photography as a parameter of private photographic self-expression. Other questions that the authors ponder in the volume are: Which functions and meanings do images have for the communications between users on social network sites? To what extent could certain design characteristics in the image-based communication on sns establish themselves as prototypical staging patterns? Which staging traditions are followed thereby? Which staging strategies are followed on different online platforms by the users' (self) visualizations

Expertise and Knowledge in the Age of Personalized Media: The Case of @anysports.faceonline Blog in the Period from 2018 to 2019

Digital age, that we are living in, enables us to instantly access great volumes of various information. The way we acquire, create and distribute knowledge is a subject to continuous transformation caused by the rapid growth of digital content and tools. Nowadays, more and more people give their own contribution in digital knowledge environment by producing and sharing their digital content. This thesis considers the impact that digital culture has put on the way we consume and create knowledge and establish the image of trustworthy expert in a certain field. This research is a case study of the Instagram account @anysports.faceonline. It represents a qualitative research aiming to analyze visual rhetoric and knowledge representation in the @anysports.faceonline blog in order to examine the mechanics of impression management, concerning the establishment and gaining acknowledgement of professionalism / expertise within online environment. By visual rhetoric is meant, in the first place, a form of visual communication the influencer uses. It involves the visual structure, displaying of information, color usage and designing of self-representation. Moreover, this research is not constrained in cultural history only, it refers to other fields such as psychology, sociology, marketing, media and gender studies. However, in order to explain the chosen visual strategies, the object of the research is, firstly, put into a broad cultural context