AFFECTME · Affective multimodal engagement
6РП — Действия „Мария Кюри“
- Период
- 2007-08-01 → 2009-07-31
- Финансиране от ЕС
- 80 000 €
- Участници
- 1
- Схема
- IRG
Линиите свързват координатора с партньорите.
Накратко на български
Емоциите на хората се изследват чрез автоматично разпознаване на езика на тялото, например при пациенти по време на физиотерапия. Това помага на компютрите да разпознават и предизвикват човешки емоции, вместо да разчитат само на лицеви изрази и думи.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Final Activity Report Summary - AFFECTME (Affective Multimodal Engagement)
In today's society, computers are increasingly present in our daily life. Affective computing is about empowering computers with the ability to recognise as well as elicit user emotions. So far, most of the research has been concentrating on facial and verbal cues as these have long been thought to be most important. The focus of this research, instead, is on bodily expressions of affect, and how they can be automatically recognised. The main achievements of this project over the last two years are three-fold: 1. Creation of a corpus of affective postures for use by the affective computing community. A large set of postures was collected across different scenarios, from chronic pain patients during physiotherapy exercises through various types of whole-body game players. Different case studies were designed to cover the various factors that elicit a large variety of affective bodily expressions, in particular, level of interest (whether the person is immersed or not), social context (whether the task is co-operative or individual), effort (whether the task is physically demanding or not). The affective states conveyed by these postures were labelled using affective categories and various affective dimensions (e.g., arousal). The corpus is being continuously updated and is made available upon request on the project website http://www.uclic.ucl.ac.uk/people/n.berthouze/AffectME.html as well as on the EU-funded HUMAINE portal http://emotion-research.net/. 2. Development of techniques for the automatic recognition of non-acted affective postures. A novel approach to the automatic classification of these postures based on low-level descriptions of their features was developed, using various state-of-the-art computational modelling techniques. To validate this approach, a benchmark was created that is based on human recognition performance. Our system was shown to perform as well as human participants in discriminating between complex affective states such as concentration, frustration or triumph. 3. Understanding of the relation between body movement and engagement in games. A recent trend in the development of games has been to offer whole-body game controllers. To date, the relationship between the use of whole-body control and level of engagement in games has not been evaluated. In a series of case studies, we studied the emotional and social components of gaming experience when using whole-body controllers. We proposed a model for the interaction between game-controller, body movement and four known engagement components (hard fun, easy fun, emotional state and social experience). This model has important implications for the design of games (e.g., exertion games) as it provides a principled approach for designing interactions leading to specific levels of engagement. Additionally, it was shown that body movements can be used to measure quality and level of engagement of players, which should be useful to the gaming industry.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
The long-term aim of this project is to contribute to the development of technologies that improve the sense of engagement of their users (positive usability) by taking into account their affective states. The proposal describes a comprehensive framework for the study of affective postural displays as an indicator of human affective states.The proposed project has three goals. The first goal is to define a computationally tractable model of emotion in which emotion is described in terms of the intensities of its autonomic response, its communicative intent, and the influence of cultural factors. These factors reflect the physiological nature of emotions and the known influence of social and task context. To address the scarcity of data in this area, we aim to collect posture data in a quantitative and principled manner, through three case studies that systematically vary the three factors of our putative model, either individually or in combination.A major difficulty in constructing our model is how to accurately determine the intended signal of affective displays. Thus, the second goal of this project is to propose a robust alternative to the methods currently used in the literature. We propose multi-modal cross-validation, that is complementing the motion capture data with recordings from other modalities such as bio-feedback and eye-tracking, and studying the perception of synthetic avatars in which the congruence of different modalities of emotion expression (e.g., facial expressions and body postures) is manipulated.The completion of those two steps will open the way for the final goal of this project, that is, the design and implementation of a computational model for the contextual recognition of affect from body posture. This is an essential step toward designing systems that can recognize, and therefore regulate, the affective states of their users.
Оригинален текст от CORDIS (на английски).
Участници
- UNIVERSITY COLLEGE LONDON · LONDONКоординаторОбединеното кралство
Връзки
Данни: CORDIS, © Европейски съюз
