846 resultados para FACIAL EMOTIONS
Resumo:
The return of emotions to debates about crime and criminal justice has been a striking development of recent decades across many jurisdictions. This has been registered in the return of shame to justice procedures, a heightened focus on victims and their emotional needs, fear of crime as a major preoccupation of citizens and politicians, and highly emotionalised public discourses on crime and justice. But how can we best make sense of these developments? Do we need to create "emotionally intelligent" justice systems, or are we messing recklessly with the rational foundations of liberal criminal justice? This volume brings together leading criminologists and sociologists from across the world in a much needed conversation about how to re-calibrate reason and emotion in crime and justice today. The contributions range from the micro-analysis of emotions in violent encounters to the paradoxes and tensions that arise from the emotionalisation of criminal justice in the public sphere. They explore the emotional labour of workers in police and penal institutions, the justice experiences of victims and offenders, and the role of vengeance, forgiveness and regret in the aftermath of violence and conflict resolution. The result is a set of original essays which offer a fresh and timely perspective on problems of crime and justice in contemporary liberal democracies.
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Automated feature extraction and correspondence determination is an extremely important problem in the face recognition community as it often forms the foundation of the normalisation and database construction phases of many recognition and verification systems. This paper presents a completely automatic feature extraction system based upon a modified volume descriptor. These features form a stable descriptor for faces and are utilised in a reversible jump Markov chain Monte Carlo correspondence algorithm to automatically determine correspondences which exist between faces. The developed system is invariant to changes in pose and occlusion and results indicate that it is also robust to minor face deformations which may be present with variations in expression.
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Analyzing emotional states under duress or during heightened, life-and-death situations is extremely difficult, especially given the inability of laboratory experiments to replicate the environment and given the inherent biases of post event surveys. This is where natural experiments, such as the pager communications from September 11th can provide the kind of natural experiment emotion researchers have been seeking. We demonstrate that positive and pro-social communications are the first to emerge followed by the slower and lower negative communications. Religious sentiment is the last to emerge, as individual attempt to make sense of event. Additionally we provide a methodological discussion about the preparation and analysis of such natural experiments (the pager message content) and show the importance of using multiple methods to extract the broadest possible understanding.
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Classroom emotional climates are interrelated with students’ engagement with university courses. Despite growing interest in emotions and emotional climate research, little is known about the ways in which social interactions and different subject matter mediate emotional climates in preservice science teacher education classes. In this study we investigated the emotional climate and associated classroom interactions in a preservice science teacher education class. We were interested in the ways in which salient classroom interactions were related to the emotional climate during lessons centered on debates about science-based issues (e.g., nuclear energy alternatives). Participants used audience response technology to indicate their perceptions of the emotional climate. Analysis of conversation for salient video clips and analysis of non-verbal conduct (acoustic parameters, body movements, and facial expressions) supplemented emotional climate data. One key contribution that this study makes to preservice science teacher education is to identify the micro-processes of successful and unsuccessful class interactions that were associated with positive and neutral emotional climate. The structure of these interactions can inform the practice of other science educators who wish to produce positive emotional climates in their classes. The study also extends and explicates the construct of intensity of emotional climate.
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Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.
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Techniques to improve the automated analysis of natural and spontaneous facial expressions have been developed. The outcome of the research has applications in several fields including national security (eg: expression invariant face recognition); education (eg: affect aware interfaces); mental and physical health (eg: depression and pain recognition).
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The affective communication patterns of conversations on Twitter can provide insights into the culture of online communities. In this paper we apply a combined quantitative and qualitative approach to investigate the structural make-up and emotional content of tweeting activity around the hashtag #auspol (for Australian politics) in order to highlight the polarity and conservativism that characterise this highly active community of politically engaged individuals. We document the centralised structure of this particular community, which is based around a deeply committed core of contributors. Through in-depth content analysis of the tweets of participants to the online debate we explore the communicative tone, patterns of engagement and thematic drivers that shape the affective character of the community and their effect on its cohesiveness. In this way we provide a comprehensive account of the complex techno-social, linguistic and cultural factors involved in conversations that are shaped in the Twittersphere.
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This paper explores the emotional life of fly‑in fly‑out (FIFO) workers and their families, through an analysis of more than 500 postings made on an online chat forum for mining families. Building on literature on fly‑in fly‑out workers and understandings of emotions as socially constructed, analysis shows how posters to the forum, typically women whose male partners are FIFO workers, construct gendered emotional identities for their partners (sometimes referred to as 'Mr Miner'), and for themselves, as 'mining women', 'mining widows' or the 'mining missus'. Inherent in the creation of gendered emotional subject positions is the process of women undertaking emotion work on and behalf of themselves, their male partners and their children. The findings demonstrate the overarching normative dimensions of women's emotional self‑transformations in the service of their mining partners' careers and the attendant reproduction of everyday patriarchal relations in the private lives of mining families.
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Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.
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The advent of the Internet of Things creates an interest in how people might interrelate through and with networks of internet enabled objects. With an emphasis on fostering social connection and physical activity among older people, this preliminary study investigated objects that people over the age of 65 years viewed as significant to them. We conducted contextual interviews in people's homes about their significant objects in order to understand the role of the objects in their lives, the extent to which they fostered emotional and social connections and physical activity, and how they might be augmented through internet connection. Discussion of significant objects generated considerable emotion in the participants. We identified objects of comfort and routine, objects that exhibited status, those that fostered independence and connection, and those that symbolized relationships with loved ones. These findings lead us to consider implications for the design of interconnected objects.
Resumo:
The role of emotion during learning encounters in science teacher education is under-researched and under-theorized. In this case study we explore the emotional climates, that is, the collective states of emotional arousal, of a preservice secondary science education class to illuminate practice for producing and reproducing high quality learning experiences for preservice science teachers. Theories related to the sociology of emotions informed our analyses from data sources such as preservice teachers’ perceptions of the emotional climate of their class, emotional facial expressions, classroom conversations, and cogenerative dialogue. The major outcome from our analyses was that even though preservice teachers reported high positive emotional climate during the professor’s science demonstrations, they also valued the professor’s in the moment reflections on her teaching that were associated with low emotional climate ratings. We co-relate emotional climate data and preservice teachers’ comments during cogenerative dialogue to expand our understanding of high quality experiences and emotional climate in science teacher education. Our study also contributes refinements to research perspectives on emotional climate.
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We employed a novel cuing paradigm to assess whether dynamically versus statically presented facial expressions differentially engaged predictive visual mechanisms. Participants were presented with a cueing stimulus that was either the static depiction of a low intensity expressed emotion; or a dynamic sequence evolving from a neutral expression to the low intensity expressed emotion. Following this cue and a backwards mask, participants were presented with a probe face that displayed either the same emotion (congruent) or a different emotion (incongruent) with respect to that displayed by the cue although expressed at a high intensity. The probe face had either the same or different identity from the cued face. The participants' task was to indicate whether or not the probe face showed the same emotion as the cue. Dynamic cues and same identity cues both led to a greater tendency towards congruent responding, although these factors did not interact. Facial motion also led to faster responding when the probe face was emotionally congruent to the cue. We interpret these results as indicating that dynamic facial displays preferentially invoke predictive visual mechanisms, and suggest that motoric simulation may provide an important basis for the generation of predictions in the visual system.
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Emotionally arousing events can distort our sense of time. We used mixed block/event-related fMRI design to establish the neural basis for this effect. Nineteen participants were asked to judge whether angry, happy and neutral facial expressions that varied in duration (from 400 to 1,600 ms) were closer in duration to either a short or long duration they learnt previously. Time was overestimated for both angry and happy expressions compared to neutral expressions. For faces presented for 700 ms, facial emotion modulated activity in regions of the timing network Wiener et al. (NeuroImage 49(2):1728–1740, 2010) namely the right supplementary motor area (SMA) and the junction of the right inferior frontal gyrus and anterior insula (IFG/AI). Reaction times were slowest when faces were displayed for 700 ms indicating increased decision making difficulty. Taken together with existing electrophysiological evidence Ng et al. (Neuroscience, doi: 10.3389/fnint.2011.00077, 2011), the effects are consistent with the idea that facial emotion moderates temporal decision making and that the right SMA and right IFG/AI are key neural structures responsible for this effect.