86,414 research outputs found
Affective games:a multimodal classification system
Affective gaming is a relatively new field of research that exploits human emotions to influence gameplay for an enhanced player experience. Changes in player’s psychology reflect on their behaviour and physiology, hence recognition of such variation is a core element in affective games. Complementary sources of affect offer more reliable recognition, especially in contexts where one modality is partial or unavailable. As a multimodal recognition system, affect-aware games are subject to the practical difficulties met by traditional trained classifiers. In addition, inherited game-related challenges in terms of data collection and performance arise while attempting to sustain an acceptable level of immersion. Most existing scenarios employ sensors that offer limited freedom of movement resulting in less realistic experiences. Recent advances now offer technology that allows players to communicate more freely and naturally with the game, and furthermore, control it without the use of input devices. However, the affective game industry is still in its infancy and definitely needs to catch up with the current life-like level of adaptation provided by graphics and animation
The perception of emotion in artificial agents
Given recent technological developments in robotics, artificial intelligence and virtual reality, it is perhaps unsurprising that the arrival of emotionally expressive and reactive artificial agents is imminent. However, if such agents are to become integrated into our social milieu, it is imperative to establish an understanding of whether and how humans perceive emotion in artificial agents. In this review, we incorporate recent findings from social robotics, virtual reality, psychology, and neuroscience to examine how people recognize and respond to emotions displayed by artificial agents. First, we review how people perceive emotions expressed by an artificial agent, such as facial and bodily expressions and vocal tone. Second, we evaluate the similarities and differences in the consequences of perceived emotions in artificial compared to human agents. Besides accurately recognizing the emotional state of an artificial agent, it is critical to understand how humans respond to those emotions. Does interacting with an angry robot induce the same responses in people as interacting with an angry person? Similarly, does watching a robot rejoice when it wins a game elicit similar feelings of elation in the human observer? Here we provide an overview of the current state of emotion expression and perception in social robotics, as well as a clear articulation of the challenges and guiding principles to be addressed as we move ever closer to truly emotional artificial agents
Exploring the Affective Loop
Research in psychology and neurology shows that both body and mind are
involved when experiencing emotions (Damasio 1994, Davidson et al.
2003). People are also very physical when they try to communicate their
emotions. Somewhere in between beings consciously and unconsciously
aware of it ourselves, we produce both verbal and physical signs to make
other people understand how we feel. Simultaneously, this production of
signs involves us in a stronger personal experience of the emotions we
express.
Emotions are also communicated in the digital world, but there is little
focus on users' personal as well as physical experience of emotions in
the available digital media. In order to explore whether and how we can
expand existing media, we have designed, implemented and evaluated
/eMoto/, a mobile service for sending affective messages to others. With
eMoto, we explicitly aim to address both cognitive and physical
experiences of human emotions. Through combining affective gestures for
input with affective expressions that make use of colors, shapes and
animations for the background of messages, the interaction "pulls" the
user into an /affective loop/. In this thesis we define what we mean by
affective loop and present a user-centered design approach expressed
through four design principles inspired by previous work within Human
Computer Interaction (HCI) but adjusted to our purposes; /embodiment/
(Dourish 2001) as a means to address how people communicate emotions in
real life, /flow/ (Csikszentmihalyi 1990) to reach a state of
involvement that goes further than the current context, /ambiguity/ of
the designed expressions (Gaver et al. 2003) to allow for open-ended
interpretation by the end-users instead of simplistic, one-emotion
one-expression pairs and /natural but designed expressions/ to address
people's natural couplings between cognitively and physically
experienced emotions. We also present results from an end-user study of
eMoto that indicates that subjects got both physically and emotionally
involved in the interaction and that the designed "openness" and
ambiguity of the expressions, was appreciated and understood by our
subjects. Through the user study, we identified four potential design
problems that have to be tackled in order to achieve an affective loop
effect; the extent to which users' /feel in control/ of the interaction,
/harmony and coherence/ between cognitive and physical expressions/,/
/timing/ of expressions and feedback in a communicational setting, and
effects of users' /personality/ on their emotional expressions and
experiences of the interaction
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