Cross-cultural research on facial expression and the developments of methods to measure facial expression are briefly summarized. What has been learned about emotion from this work on the face is then elucidated. Four questions about facial expression and emotion are discussed. What information does an expression typically convey? Can there be emotion without facial expression? Can there be a facial expression of emotion without emotion? How do individuals differ in their facial expressions of emotion? In 1965 when 1 began to study facial expression, 1 few thought there was much to be learned. Goldstein (1981) pointed out that a number of famous psychologists—F. and G. Allport, Brunswik, Hull, Lindzey, Maslow, Osgood, Titchner—did only one facial study, which was not what earned them their reputations. Harold Schlosberg was an exception, but he was more interested in how to represent the information derived by those who observed the face than in expression itself. 2 The face was considered a meager source of mostly inaccurate, culturespecific, stereotypical information (Bruner & Tagiuri, 1954). That this contradicted what every layman knew made it all the more attractive. Psychology had exposed the falseness of a folk belief, a counterintuitive finding.

Facial expressions provide an important behavioral measure for the study of emotion, cognitive processes, and social interaction. The Facial Action Coding System ~Ekman & Friesen, 1978! is an objective method for quantifying facial movement in terms of component actions. We applied computer image analysis to the problem of automatically detecting facial actions in sequences of images. Three approaches were compared: holistic spatial analysis, explicit measurement of features such as wrinkles, and estimation of motion flow fields. The three methods were combined in a hybrid system that classified six upper facial actions with 91 % accuracy. The hybrid system outperformed human nonexperts on this task and performed as well as highly trained experts. An automated system would make facial expression measurement more widely accessible as a research tool in behavioral science and investigations of the neural substrates of emotion.

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Emotions are universally recognized from facial expressions—or so it has been claimed. To support that claim, research has been carried out in various modern cultures and in cultures relatively isolated from Western influence. A review of the methods used in that research raises questions of its ecological, convergent, and internal validity. Forced-choice response format, within-subject design, preselected photographs of posed facial expressions, and other features of method are each problematic. When they are altered, less supportive or nonsupportive results occur. When they are combined, these method factors may help to shape the results. Facial expressions and emotion labels are probably associated, but the association may vary with culture and is loose enough to be consistent with various alternative accounts, 8 of which are discussed. "Everyone knows that grief involves a gloomy and joy a cheerful countenance.... There are characteristic facial expressions which are observed to accompany anger, fear, erotic excitement, and all the other passions " (Aristotle, nd/1913, pp. 805, 808). Aristotle was not proposing a new idea but was cataloging what was known on the topic of physiognomy. The theory was that a person's physical appearance, especially in the face, reveals deeper characteristics: Poor proportions reveal a rogue, soft hair a coward, and a smile a happy person.' Today, few psychologists share Aristotle's belief about the meaning of poor proportions or soft hair, but many share his beliefs about facial expression and emotion. Oatley and Jenkins (1992) observed, "By far the most extensive body of data in the field of human emotions is that on facial expressions of emotion" (p. 67). Recent reviews of those data (see Table 1) agree that the face reveals emotion in a way that is universally understood: Happiness, surprise, fear, anger, contempt, disgust, and sadness—these seven emotions, plus or minus two, are recognized from facial expressions by all human beings, regardless of their cultural background.

This paper presents the role of ethological and emotional models as the basis for an architecture in support of entertainment robotic systems. Specific examples for Sony’s AIBO are presented as well as extensions related to a new humanoid robot, SDR. I.

Emotion is a fundamental component of being human. Joy, hate, anger, and pride, among the plethora of other emotions, motivate action and add meaning and richness to virtually all human experience. Traditionally, human-computer interaction has been viewed as the “ultimate ” exception: Users must discard their emotional selves to work efficiently and rationality with computers, the quintessentially unemotional artifact. Emotion seemed at best marginally relevant to human-computer interaction―and at worst oxymoronic. Recent research in psychology and technology suggests a very different view of the relationship between humans, computers, and emotion. After a long period of dormancy and confusion, there has been an explosion of research on the psychology of emotion (Gross, 1999). Emotion is no longer seen as limited to the occasional outburst of fury when a computer crashes inexplicably, excitement when a videogame character leaps past an obstacle, or frustration at an incomprehensible error message. It is now understood that a wide range of emotions plays a critical role in every computer-related, goal-directed activity, from developing a 3-D CAD model and running calculations on a spreadsheet, to searching the Web and sending an email, to making an online purchase and playing solitaire. Indeed, many psychologists now argue that it is

ample, may see a fly, and, therefore, have the potentiality of flicking its tongue in a certain way followed by eating. But it may simultaneously see the shadow of a hawk overhead, in which case it also has the selection option of jumping into the water. Both potentialities must be somehow indicated to or for the frog so that a selection between them can occur. Furthermore, if the hawk shadow is not present and the frog misses the fly, it may be advantageous to detect that failure of the tongue flicking action and, on the basis of that detection, to make a further selection of interaction. That further selection might be to try again, or might be to move to a different location where flies are perhaps more numerous or slower. It can be advantageous, in other words, to be able to detect failures of actions, as well as to be able to select among potential actions. A slight addition to the ability to indicate potential interactions suffices to allow such error detection. In pa

ABSTRACT: Nonverbal behaviors in response to viewing slides depicting nude males, nude females, erotic couples and neutral pictures, either alone or in the presence of two unfamiliar individuals, were studied in 22 female and 16 male university students. Participants were unaware of being videorecorded. Results revealed discrepancies between self-reported embarrassment and nonverbal behaviors supposedly expressive of embarrassment. Although self-reported embarrassment was higher when certain types of slides were viewed in the presence of others than when they were viewed alone, we observed significantly fewer lip movements, gaze shifts, face touches, downward gazes, and downward head movements in the presence of unfamiliar individuals than in the alone condition. We also compared behaviors during slide exposure and during the inter-slide intervals. For 9 out of 11 coded behaviors, frequencies were significantly higher during inter-slide intervals than during slide presentation. We argue that this is probably due to the fact that visual attention to the slides inhibited nonverbal behaviors. The results cast doubt on the possibility of inferring the internal state of an emotion such as embarrassment

This report describes the results of automated facial expression analysis by the CMU/Pittsburgh group. An interdisciplinary team of consultants, who have combined expertise in computer vision and in facial analysis, will compare the results of this report with those in a separate report submitted by UCSD group. BACKGROUND People communicate not only by speech and written language but also by their tone of voice, the way they stand or move and their patterns of gaze. These modes of nonverbal behavior communicate emotion and often are referred to as paralinguistic because they modify, substitute for, and improve the understanding of spoken communication. Of the various modes of nonverbal communication, the human face is especially important. Facial expressions can indicate emotion and pain, regulate social behavior, and reveal brain function. A large literature in psychology (Ekman & Rosenberg, 1997), comparative biology (Darwin, 1872/1998; Fridlund, 1994; Schmidt & Coh