Recent & Upcoming Talks

ABSTRACT: In the wake of rapid advances in automatic affect analysis, commercial automatic classifiers for facial affect recognition have attracted considerable attention in recent years. While several options now exist to analyse dynamic video data, less is known about the relative performance of these classifiers, in particular when facial expressions are spontaneous rather than posed.

ABSTRACT: With the development of IoT and Machine Learning, it is now possible to automatically evaluate emotions from various data streams among which facial expressions are one of the most prominent.

ABSTRACT: Understanding the characteristics of the housing market is essential for both sellers and buyers. However, the housing market is influenced by multiple factors. In this paper, the urban and socio-economic structure of an area is used to predict the price of 10387 properties sold in 2018 in the city of Dublin.

ABSTRACT: Emotions are a main driver of decision making processes; their understanding is essential to produce consumer’s insights. With the development of IoT and Machine Learning, it is now possible to automatically evaluate emotions from various data streams among which facial expressions are one of the most prominent.

ABSTRACT: Voice is one of the main communicative sources of evidence in interpreting the expression of emotion. Affective computing aims to create systems and algorithms that automatically analyse people’s emotional state.

ABSTRACT: Sharing personal information is an important way of communicating on social media. Among the information possibly shared, new sensors and tools allow people to share emotion information via facial emotion recognition.

ABSTRACT: The analysis of facial expressions is currently a favoured method of inferring experienced emotion, and consequently significant efforts are currently being made to develop improved facial expression recognition techniques. Among these new techniques, those which allow the automatic recognition of facial expression appear to be most promising.

ABSTRACT: With the development of wearable sensors, it is now possible to assess the dynamic progression of physiological rhythms such as heart rate, breathing rate or galvanic skin response in ways and places and during certain activities that were previously not possible due to cost and reliability.

SYMPOSIUM 2: Affect Recognition in Humans versus Machines: Current Issues and Future Challenges Convener: Eva Krumhuber, University College London, UK ABSTRACT: Automatic facial expression recognition systems can provide important information about our emotions and how they change over time.

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ABSTRACT: With the development of wearable sensors, it is now possible to assess the dynamic progression of physiological rhythms such as heart rate, breathing rate or galvanic skin response in ways and places that were previously impractical.

ABSTRACT: With the development of wearable sensors, it is now possible to assess the dynamic progression of physiological rhythms such as heart rate, breathing rate or galvanic skin response in ways and places and during certain activities that were previously not possible due to cost and reliability.

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ABSTRACT: User eXperience studies with products, systems or services have significantly increased in companies in order to anticipate their commercial success. Among the user experience dimensions, emotions are predominant. However User eXperience studies used several concepts to refer to emotions and current measures still have some flaws.

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ABSTRACT: In supporting the visual-mediated emotional recognition, little research has centred on analysing the effect of presenting different combinatorial facial designs. Moreover, in the theoretical field of emotions, research on the recognition of emotional facial expressions (EFE) is mainly based on static and posed databases tested in unnatural contexts (explicit recognition task of an emotion).

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