Browsing by Author "Ho, Chin-Chang"

Now showing 1 - 8 of 8
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    The Aesthetic Dimensions of U.S. and South Korean Responses to Web Home Pages: A Cross-Cultural Comparison
    (2011-01) Faiola, Anthony; Ho, Chin-Chang; Tarrant, Mark D.; MacDorman, Karl F.
    Culturally influenced preferences in website aesthetics is a topic often neglected by scholars in human-computer interaction. Kim, Lee, and Choi (2003) identified aesthetic design factors of web home pages that elicited particular responses in South Korean web users based on 13 secondary emotional dimensions. This study extends Kim et al.'s work to U.S. participants, comparing the original South Korean findings with U.S. findings. Results show that U.S. participants reliably applied translations of the emotional adjectives used in the South Korean study to the home pages. However, factor analysis revealed that the aesthetic perceptions of U.S. and South Korean participants formed different aesthetic dimensions composed of different sets of emotional adjectives, suggesting that U.S. and South Korean people perceive the aesthetics of home pages differently. These results indicate that website aesthetics can vary significantly between cultures.
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    The appearance, speech, and motion of synthetic humans influences our empathy toward them
    (Office of the Vice Chancellor for Research, 2011-04-08) MacDorman, Karl F.; Ho, Chin-Chang; Lu, Amy S.; Mitchell, Wade J.; Patel, Himalaya; Srinivas, Preethi; Schermerhorn, Paul W.; Scheutz, Matthias
    Humanoid robots and computer-generated humans can elicit responses that people usually direct toward each other. As a result these humanlike entities may stand in for human actors during experiment-driven research in the social and psychological sciences as well as in some branches of neuroscience. Such research concerns factors like facial appearance, physical embodiment, speech quality, fluidity of motion, and contingent interactivity. A goal of this research is to understand why some humanlike entities are more successful than others at eliciting people’s empathy. Pursuing this goal informs new principles for creating synthetic humans that seem more believable in narratives and narrative-based interventions.
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    Human Emotion and the Uncanny Valley: A Glm, Mds, and Isomap Analysis of Robot Video Ratings
    Ho, Chin-Chang; MacDorman, Karl F.
    The eerie feeling attributed to human-looking robots and animated characters may be a key factor in our perceptual and cognitive discrimination between the human and the merely humanlike. This study applies factor analysis, correlation, the generalized linear model (GLM), multidimensional scaling (MDS), and kernel isometric mapping (ISOMAP) to analyze ratings of 27 emotions of 16 moving figures whose appearance varies along a human likeness continuum. The results indicate (1) Attributions of eerie and creepy better capture human visceral reaction to an uncanny robot than strange. (2) Eeriness and creepiness are mainly associated with fear but also shocked, disgusted, and nervous. Strange and humanlike are less strongly associated with emotion. (3) Thus, strange and humanlike may be more cognitive, while eerie and creepy are more perceptual and emotional. (4) Human and facial features increase ratings of human likeness. (5) Women are slightly more sensitive to eerie and creepy than men; and older people may be more willing to attribute human likeness to a robot despite its eeriness.
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    Human emotions toward stimuli in the uncanny valley: laddering and index construction
    (2015) Ho, Chin-Chang; MacDorman, Karl F.; Pfaff, Mark S.; Fedorikhin, Alexander; Huang, Edgar
    Human-looking computer interfaces, including humanoid robots and animated humans, may elicit in their users eerie feelings. This effect, often called the uncanny valley, emphasizes our heightened ability to distinguish between the human and merely humanlike using both perceptual and cognitive approaches. Although reactions to uncanny characters are captured more accurately with emotional descriptors (e.g., eerie and creepy) than with cognitive descriptors (e.g., strange), and although previous studies suggest the psychological processes underlying the uncanny valley are more perceptual and emotional than cognitive, the deep roots of the concept of humanness imply the application of category boundaries and cognitive dissonance in distinguishing among robots, androids, and humans. First, laddering interviews (N = 30) revealed firm boundaries among participants’ concepts of animated, robotic, and human. Participants associated human traits like soul, imperfect, or intended exclusively with humans, and they simultaneously devalued the autonomous accomplishments of robots (e.g., simple task, limited ability, or controlled). Jerky movement and humanlike appearance were associated with robots, even though the presented robotic stimuli were humanlike. The facial expressions perceived in robots as improper were perceived in animated characters as mismatched. Second, association model testing indicated that the independent evaluation based on the developed indices is a viable quantitative technique for the laddering interview. Third, from the interviews several candidate items for the eeriness index were validated in a large representative survey (N = 1,311). The improved eeriness index is nearly orthogonal to perceived humanness (r = .04). The improved indices facilitate plotting relations among rated characters of varying human likeness, enhancing perspectives on humanlike robot design and animation creation.
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    The human likeness of computer-generated characters predicts altercentric intrusion during a counting task (Alternative title: An uncanny valley of visual perspective taking: A study of the effects of character human likeness and eeriness on altercentric intrusion during a counting task)
    (Office of the Vice Chancellor for Research, 2011-04-08) Srinivas, Preethi; Patel, Himalaya; Ho, Chin-Chang; MacDorman, Karl F.
    Abstract: Perceivers lose empathy for synthetic human characters when the characters' nonhuman features elicit an eerie feeling. This phenomenon, termed the uncanny valley, may specifically diminish the likelihood of understanding these characters' perspective. Such perspective taking should rely on a more fundamental ability to infer a character's visual perspective merely by looking at the character. Based on this assumption, a dot-counting task was undertaken by 268 undergraduate students in which they either took or ignored the apparent field of vision of computer-drawn characters with varying human likeness. It was predicted that for characters that appear more humanlike, task trials with a similar visual perspective between participant and character would predict shorter response times and higher accuracy, whereas task trials with dissimilar visual perspectives would predict longer response times and lower accuracy. Although these predictions were supported, trials with dissimilar visual perspectives also yielded longer response times when they included certain photorealistic inanimate objects (e.g., a chair). Future studies will ascertain whether such perspective taking ability is similarly affected when the synthetic human characters are more photorealistic.
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    Measuring the Uncanny Valley Effect
    (Springer, 2017-01) Ho, Chin-Chang; MacDorman, Karl F.; BioHealth Informatics, School of Informatics and Computing
    Using a hypothetical graph, Masahiro Mori proposed in 1970 the relation between the human likeness of robots and other anthropomorphic characters and an observer’s affective or emotional appraisal of them. The relation is positive apart from a U-shaped region known as the uncanny valley. To measure the relation, we previously developed and validated indices for the perceptual-cognitive dimension humanness and three affective dimensions: interpersonal warmth, attractiveness, and eeriness. Nevertheless, the design of these indices was not informed by how the untrained observer perceives anthropomorphic characters categorically. As a result, scatter plots of humanness vs. eeriness show the stimuli cluster tightly into categories widely separated from each other. The present study applies a card sorting task, laddering interview, and adjective evaluation ( N=30 ) to revise the humanness, attractiveness, and eeriness indices and validate them via a representative survey ( N=1311 ). The revised eeriness index maintains its orthogonality to humanness ( r=.04 , p=.285 ), but the stimuli show much greater spread, reflecting the breadth of their range in human likeness and eeriness. The revised indices enable empirical relations among characters to be plotted similarly to Mori’s graph of the uncanny valley. Accurate measurement with these indices can be used to enhance the design of androids and 3D computer animated characters.
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    Probing People's Attitudes and Behaviors Using Humanlike Agents
    (Office of the Vice Chancellor for Research, 2010-04-09) MacDorman, Karl F.; Gadde, Prathik; Ho, Chin-Chang; Mitchell, Wade J.; Schermerhorn, Paul W.; Scheutz, Matthias
    Android science is an interdisciplinary framework for studying human cognition and interaction based on the finding that android robots—and, to lesser extents, humanoid robots and computergenerated humans—can elicit the sorts of responses people direct toward each other. As a result, these humanlike agents can be used as stand-ins for humans in social, psychological, cognitive, and neuroscientific experiments. We describe a selection of current and recently completed investigations into some of the potential factors influencing attitudes and behavior toward humanlike agents, including facial appearance, physical embodiment, speech quality, fluidity of motion, and contingent interactivity.
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    Too real for comfort? Uncanny responses to computer generated faces
    (ScienceDirect, 2014-12-12) MacDorman, Karl F.; Green, Robert D.; Ho, Chin-Chang; Koch, Clinton T.; Department of Human-Centered Computing, IU School of Informatics and Computing
    As virtual humans approach photorealistic perfection, they risk making real humans uncomfortable. This intriguing phenomenon, known as the uncanny valley, is well known but not well understood. In an effort to demystify the causes of the uncanny valley, this paper proposes several perceptual, cognitive, and social mechanisms that have already helped address riddles like empathy, mate selection, threat avoidance, cognitive dissonance, and psychological defenses. In the four studies described herein, a computer generated human character’s facial proportions, skin texture, and level of detail were varied to examine their effect on perceived eeriness, human likeness, and attractiveness. In Study I, texture photorealism and polygon count increased human likeness. In Study II, texture photorealism heightened the accuracy of human judgments of ideal facial proportions. In Study III, atypical facial proportions were shown to be more disturbing on photorealistic faces than on other faces. In Study IV, a mismatch in the size and texture of the eyes and face was especially prone to make a character eerie. These results contest the depiction of the uncanny valley as a simple relation between comfort level and human likeness. This paper concludes by introducing a set of design principles for bridging the uncanny valley.